Diamond Price Prediction .ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f0ca937f-f2c8-4351-9f69-d3c0727437f3",
   "metadata": {},
   "source": [
    "### Import Librarries "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0eb197d4-3c81-4021-ab49-618a0d02fc1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns\n",
    "import plotly.express as px\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "033b9056-01b3-4154-9118-28108187bd9f",
   "metadata": {},
   "source": [
    "## Read Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "792b8f1b-faa2-461d-83ce-75e10f0bfcb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('Diamond Price.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bb8dfd4-bc5b-46c3-9bbf-419dfdef8a32",
   "metadata": {},
   "source": [
    "## Get information about data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fbe20f62-3f37-475b-8b70-dcb21fc6bf3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Carat(Weight of Daimond)</th>\n",
       "      <th>Cut(Quality)</th>\n",
       "      <th>Color</th>\n",
       "      <th>Clarity</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Table</th>\n",
       "      <th>Price(in US dollars)</th>\n",
       "      <th>X(length)</th>\n",
       "      <th>Y(width)</th>\n",
       "      <th>Z(Depth)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS1</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65.0</td>\n",
       "      <td>327</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>334</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>335</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Carat(Weight of Daimond) Cut(Quality) Color Clarity  Depth  Table  \\\n",
       "0                      0.23        Ideal     E     SI2   61.5   55.0   \n",
       "1                      0.21      Premium     E     SI1   59.8   61.0   \n",
       "2                      0.23         Good     E     VS1   56.9   65.0   \n",
       "3                      0.29      Premium     I     VS2   62.4   58.0   \n",
       "4                      0.31         Good     J     SI2   63.3   58.0   \n",
       "\n",
       "   Price(in US dollars)  X(length)  Y(width)  Z(Depth)  \n",
       "0                   326       3.95      3.98      2.43  \n",
       "1                   326       3.89      3.84      2.31  \n",
       "2                   327       4.05      4.07      2.31  \n",
       "3                   334       4.20      4.23      2.63  \n",
       "4                   335       4.34      4.35      2.75  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "974b67c0-bb73-43a7-a2b1-20dc3f998ca1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 53940 entries, 0 to 53939\n",
      "Data columns (total 10 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Carat(Weight of Daimond)  53940 non-null  float64\n",
      " 1   Cut(Quality)              53940 non-null  object \n",
      " 2   Color                     53940 non-null  object \n",
      " 3   Clarity                   53940 non-null  object \n",
      " 4   Depth                     53940 non-null  float64\n",
      " 5   Table                     53940 non-null  float64\n",
      " 6   Price(in US dollars)      53940 non-null  int64  \n",
      " 7   X(length)                 53940 non-null  float64\n",
      " 8   Y(width)                  53940 non-null  float64\n",
      " 9   Z(Depth)                  53940 non-null  float64\n",
      "dtypes: float64(6), int64(1), object(3)\n",
      "memory usage: 4.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "49894988-423f-4936-97d0-ce3d86f21860",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Carat(Weight of Daimond)', 'Cut(Quality)', 'Color', 'Clarity', 'Depth',\n",
       "       'Table', 'Price(in US dollars)', 'X(length)', 'Y(width)', 'Z(Depth)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e66e95eb-52f7-436d-9ed7-d6cb802c28f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = ['Weight', 'Cut_Quality', 'Color', 'Clarity', 'Depth',\n",
    "       'Table', 'Price', 'X_length', 'Y_width', 'Z_Depth']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a27ff25b-631e-4e33-9f6d-0347edeef408",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Weight</th>\n",
       "      <th>Cut_Quality</th>\n",
       "      <th>Color</th>\n",
       "      <th>Clarity</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Table</th>\n",
       "      <th>Price</th>\n",
       "      <th>X_length</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>E</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.98</td>\n",
       "      <td>2.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.21</td>\n",
       "      <td>Premium</td>\n",
       "      <td>E</td>\n",
       "      <td>SI1</td>\n",
       "      <td>59.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>326</td>\n",
       "      <td>3.89</td>\n",
       "      <td>3.84</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>VS1</td>\n",
       "      <td>56.9</td>\n",
       "      <td>65.0</td>\n",
       "      <td>327</td>\n",
       "      <td>4.05</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.29</td>\n",
       "      <td>Premium</td>\n",
       "      <td>I</td>\n",
       "      <td>VS2</td>\n",
       "      <td>62.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>334</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.31</td>\n",
       "      <td>Good</td>\n",
       "      <td>J</td>\n",
       "      <td>SI2</td>\n",
       "      <td>63.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>335</td>\n",
       "      <td>4.34</td>\n",
       "      <td>4.35</td>\n",
       "      <td>2.75</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>53935</th>\n",
       "      <td>0.72</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>60.8</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.75</td>\n",
       "      <td>5.76</td>\n",
       "      <td>3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53936</th>\n",
       "      <td>0.72</td>\n",
       "      <td>Good</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>63.1</td>\n",
       "      <td>55.0</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.69</td>\n",
       "      <td>5.75</td>\n",
       "      <td>3.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53937</th>\n",
       "      <td>0.70</td>\n",
       "      <td>Very Good</td>\n",
       "      <td>D</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.8</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.66</td>\n",
       "      <td>5.68</td>\n",
       "      <td>3.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53938</th>\n",
       "      <td>0.86</td>\n",
       "      <td>Premium</td>\n",
       "      <td>H</td>\n",
       "      <td>SI2</td>\n",
       "      <td>61.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>2757</td>\n",
       "      <td>6.15</td>\n",
       "      <td>6.12</td>\n",
       "      <td>3.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53939</th>\n",
       "      <td>0.75</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>SI2</td>\n",
       "      <td>62.2</td>\n",
       "      <td>55.0</td>\n",
       "      <td>2757</td>\n",
       "      <td>5.83</td>\n",
       "      <td>5.87</td>\n",
       "      <td>3.64</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>53940 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Weight Cut_Quality Color Clarity  Depth  Table  Price  X_length  \\\n",
       "0        0.23       Ideal     E     SI2   61.5   55.0    326      3.95   \n",
       "1        0.21     Premium     E     SI1   59.8   61.0    326      3.89   \n",
       "2        0.23        Good     E     VS1   56.9   65.0    327      4.05   \n",
       "3        0.29     Premium     I     VS2   62.4   58.0    334      4.20   \n",
       "4        0.31        Good     J     SI2   63.3   58.0    335      4.34   \n",
       "...       ...         ...   ...     ...    ...    ...    ...       ...   \n",
       "53935    0.72       Ideal     D     SI1   60.8   57.0   2757      5.75   \n",
       "53936    0.72        Good     D     SI1   63.1   55.0   2757      5.69   \n",
       "53937    0.70   Very Good     D     SI1   62.8   60.0   2757      5.66   \n",
       "53938    0.86     Premium     H     SI2   61.0   58.0   2757      6.15   \n",
       "53939    0.75       Ideal     D     SI2   62.2   55.0   2757      5.83   \n",
       "\n",
       "       Y_width  Z_Depth  \n",
       "0         3.98     2.43  \n",
       "1         3.84     2.31  \n",
       "2         4.07     2.31  \n",
       "3         4.23     2.63  \n",
       "4         4.35     2.75  \n",
       "...        ...      ...  \n",
       "53935     5.76     3.50  \n",
       "53936     5.75     3.61  \n",
       "53937     5.68     3.56  \n",
       "53938     6.12     3.74  \n",
       "53939     5.87     3.64  \n",
       "\n",
       "[53940 rows x 10 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1bf67e7c-6924-4928-a9f3-b742b27de91b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ideal        21551\n",
       "Premium      13791\n",
       "Very Good    12082\n",
       "Good          4906\n",
       "Fair          1610\n",
       "Name: Cut_Quality, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Cut_Quality'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "18b73835-18a2-4496-879c-fcd1938bd6ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "G    11292\n",
       "E     9797\n",
       "F     9542\n",
       "H     8304\n",
       "D     6775\n",
       "I     5422\n",
       "J     2808\n",
       "Name: Color, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Color'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2e015d38-57fa-4ffd-ba49-d37cdc0dd5d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SI1     13065\n",
       "VS2     12258\n",
       "SI2      9194\n",
       "VS1      8171\n",
       "VVS2     5066\n",
       "VVS1     3655\n",
       "IF       1790\n",
       "I1        741\n",
       "Name: Clarity, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Clarity'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "be20b337-9277-47c5-b68d-0adc1680fca3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Weight</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Table</th>\n",
       "      <th>Price</th>\n",
       "      <th>X_length</th>\n",
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       "      <th>count</th>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "      <td>53940.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.797940</td>\n",
       "      <td>61.749405</td>\n",
       "      <td>57.457184</td>\n",
       "      <td>3932.799722</td>\n",
       "      <td>5.731157</td>\n",
       "      <td>5.734526</td>\n",
       "      <td>3.538734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.474011</td>\n",
       "      <td>1.432621</td>\n",
       "      <td>2.234491</td>\n",
       "      <td>3989.439738</td>\n",
       "      <td>1.121761</td>\n",
       "      <td>1.142135</td>\n",
       "      <td>0.705699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>326.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>950.000000</td>\n",
       "      <td>4.710000</td>\n",
       "      <td>4.720000</td>\n",
       "      <td>2.910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.700000</td>\n",
       "      <td>61.800000</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>2401.000000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>5.710000</td>\n",
       "      <td>3.530000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.040000</td>\n",
       "      <td>62.500000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>5324.250000</td>\n",
       "      <td>6.540000</td>\n",
       "      <td>6.540000</td>\n",
       "      <td>4.040000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.010000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>18823.000000</td>\n",
       "      <td>10.740000</td>\n",
       "      <td>58.900000</td>\n",
       "      <td>31.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Weight         Depth         Table         Price      X_length  \\\n",
       "count  53940.000000  53940.000000  53940.000000  53940.000000  53940.000000   \n",
       "mean       0.797940     61.749405     57.457184   3932.799722      5.731157   \n",
       "std        0.474011      1.432621      2.234491   3989.439738      1.121761   \n",
       "min        0.200000     43.000000     43.000000    326.000000      0.000000   \n",
       "25%        0.400000     61.000000     56.000000    950.000000      4.710000   \n",
       "50%        0.700000     61.800000     57.000000   2401.000000      5.700000   \n",
       "75%        1.040000     62.500000     59.000000   5324.250000      6.540000   \n",
       "max        5.010000     79.000000     95.000000  18823.000000     10.740000   \n",
       "\n",
       "            Y_width       Z_Depth  \n",
       "count  53940.000000  53940.000000  \n",
       "mean       5.734526      3.538734  \n",
       "std        1.142135      0.705699  \n",
       "min        0.000000      0.000000  \n",
       "25%        4.720000      2.910000  \n",
       "50%        5.710000      3.530000  \n",
       "75%        6.540000      4.040000  \n",
       "max       58.900000     31.800000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f86d183d-2871-4aeb-875c-a36d6e5941e6",
   "metadata": {},
   "source": [
    "-------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e54aa88f-39a9-4e67-a124-fd1d6817d52a",
   "metadata": {},
   "source": [
    "## Data cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4018c0b5-2cb7-4f83-95c0-f9bf5fd7d5db",
   "metadata": {},
   "source": [
    "--------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e33336c-b597-4b05-8e4b-865148e5cd7d",
   "metadata": {},
   "source": [
    "### duplicates handling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ad4afac8-6585-4443-a06e-2889b89e04cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Weight</th>\n",
       "      <th>Cut_Quality</th>\n",
       "      <th>Color</th>\n",
       "      <th>Clarity</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Table</th>\n",
       "      <th>Price</th>\n",
       "      <th>X_length</th>\n",
       "      <th>Y_width</th>\n",
       "      <th>Z_Depth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>0.79</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.3</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2898</td>\n",
       "      <td>5.90</td>\n",
       "      <td>5.85</td>\n",
       "      <td>3.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1006</th>\n",
       "      <td>0.79</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.3</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2898</td>\n",
       "      <td>5.90</td>\n",
       "      <td>5.85</td>\n",
       "      <td>3.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1007</th>\n",
       "      <td>0.79</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.3</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2898</td>\n",
       "      <td>5.90</td>\n",
       "      <td>5.85</td>\n",
       "      <td>3.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1008</th>\n",
       "      <td>0.79</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>G</td>\n",
       "      <td>SI1</td>\n",
       "      <td>62.3</td>\n",
       "      <td>57.0</td>\n",
       "      <td>2898</td>\n",
       "      <td>5.90</td>\n",
       "      <td>5.85</td>\n",
       "      <td>3.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025</th>\n",
       "      <td>1.52</td>\n",
       "      <td>Good</td>\n",
       "      <td>E</td>\n",
       "      <td>I1</td>\n",
       "      <td>57.3</td>\n",
       "      <td>58.0</td>\n",
       "      <td>3105</td>\n",
       "      <td>7.53</td>\n",
       "      <td>7.42</td>\n",
       "      <td>4.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47969</th>\n",
       "      <td>0.52</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>D</td>\n",
       "      <td>VS2</td>\n",
       "      <td>61.8</td>\n",
       "      <td>55.0</td>\n",
       "      <td>1919</td>\n",
       "      <td>5.19</td>\n",
       "      <td>5.16</td>\n",
       "      <td>3.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49326</th>\n",
       "      <td>0.51</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>F</td>\n",
       "      <td>VVS2</td>\n",
       "      <td>61.2</td>\n",
       "      <td>56.0</td>\n",
       "      <td>2093</td>\n",
       "      <td>5.17</td>\n",
       "      <td>5.19</td>\n",
       "      <td>3.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49557</th>\n",
       "      <td>0.71</td>\n",
       "      <td>Good</td>\n",
       "      <td>F</td>\n",
       "      <td>SI2</td>\n",
       "      <td>64.1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2130</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50079</th>\n",
       "      <td>0.51</td>\n",
       "      <td>Ideal</td>\n",
       "      <td>F</td>\n",
       "      <td>VVS2</td>\n",
       "      <td>61.2</td>\n",
       "      <td>56.0</td>\n",
       "      <td>2203</td>\n",
       "      <td>5.19</td>\n",
       "      <td>5.17</td>\n",
       "      <td>3.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52861</th>\n",
       "      <td>0.50</td>\n",
       "      <td>Fair</td>\n",
       "      <td>E</td>\n",
       "      <td>VS2</td>\n",
       "      <td>79.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>2579</td>\n",
       "      <td>5.21</td>\n",
       "      <td>5.18</td>\n",
       "      <td>4.09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>146 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Weight Cut_Quality Color Clarity  Depth  Table  Price  X_length  \\\n",
       "1005     0.79       Ideal     G     SI1   62.3   57.0   2898      5.90   \n",
       "1006     0.79       Ideal     G     SI1   62.3   57.0   2898      5.90   \n",
       "1007     0.79       Ideal     G     SI1   62.3   57.0   2898      5.90   \n",
       "1008     0.79       Ideal     G     SI1   62.3   57.0   2898      5.90   \n",
       "2025     1.52        Good     E      I1   57.3   58.0   3105      7.53   \n",
       "...       ...         ...   ...     ...    ...    ...    ...       ...   \n",
       "47969    0.52       Ideal     D     VS2   61.8   55.0   1919      5.19   \n",
       "49326    0.51       Ideal     F    VVS2   61.2   56.0   2093      5.17   \n",
       "49557    0.71        Good     F     SI2   64.1   60.0   2130      0.00   \n",
       "50079    0.51       Ideal     F    VVS2   61.2   56.0   2203      5.19   \n",
       "52861    0.50        Fair     E     VS2   79.0   73.0   2579      5.21   \n",
       "\n",
       "       Y_width  Z_Depth  \n",
       "1005      5.85     3.66  \n",
       "1006      5.85     3.66  \n",
       "1007      5.85     3.66  \n",
       "1008      5.85     3.66  \n",
       "2025      7.42     4.28  \n",
       "...        ...      ...  \n",
       "47969     5.16     3.20  \n",
       "49326     5.19     3.17  \n",
       "49557     0.00     0.00  \n",
       "50079     5.17     3.17  \n",
       "52861     5.18     4.09  \n",
       "\n",
       "[146 rows x 10 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7f662531-e210-4da3-981a-6ed526eb718f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cb6939b-f555-473f-8242-dd0278e04e88",
   "metadata": {},
   "source": [
    "--------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "113367cf-7b62-4de4-b2bb-fcf71c2f748a",
   "metadata": {},
   "source": [
    "### null data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "87a88afa-866f-40fc-85f1-a448cfd503f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Weight         0\n",
       "Cut_Quality    0\n",
       "Color          0\n",
       "Clarity        0\n",
       "Depth          0\n",
       "Table          0\n",
       "Price          0\n",
       "X_length       0\n",
       "Y_width        0\n",
       "Z_Depth        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2483b836-60c1-457f-b64e-92fbe78770ea",
   "metadata": {},
   "source": [
    "----------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "560e2de6-eced-4b59-b77e-f76ff53a57b5",
   "metadata": {},
   "source": [
    "### Detect and remove outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a3811fca-f21d-4de5-aeb0-bc941e459c02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2200x1700 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "numeric_cols = ['Weight', 'Depth','Table', 'Price', 'X_length', 'Y_width', 'Z_Depth']\n",
    "plt.figure(figsize=(22, 17))\n",
    "for i in range(7) :\n",
    "    plt.subplot(3,3,i+1)\n",
    "    \n",
    "    sns.boxplot(x=df[numeric_cols[i]],color='#6DA59D')\n",
    "    plt.title(numeric_cols[i])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e47ce635-1ec6-4093-a723-2f69034d142b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def detect_outliers(data,column):\n",
    "    q1 = df[column].quantile(.25)\n",
    "    q3= df[column].quantile(.75)\n",
    "    IQR = q3-q1\n",
    "    \n",
    "    lower_bound = q1 - (1.5*IQR)\n",
    "    upper_bound = q3 + (1.5*IQR)\n",
    "    \n",
    "    ls = df.index[(df[column] <lower_bound) | (df[column] > upper_bound)]\n",
    "    \n",
    "    return ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d9895319-77a9-40c5-bc17-99045af13868",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "index_list = []\n",
    "\n",
    "for column in numeric_cols:\n",
    "    index_list.extend(detect_outliers(df,column))\n",
    "\n",
    "# remove duplicated indices in the index_list and sort it \n",
    "index_list = sorted(set(index_list))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "37461e69-90ac-4886-99d5-11df324e17e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "before_remove = df.shape\n",
    "df =df.drop(index_list)\n",
    "after_remove = df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8b17448a-49a6-4fb0-8c6d-3b04e65317f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of data before removing outliers : (53794, 10)\n",
      "Shape of data after remove : (47416, 10)\n"
     ]
    }
   ],
   "source": [
    "print(f'''Shape of data before removing outliers : {before_remove}\n",
    "Shape of data after remove : {after_remove}''')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5b433ec-881d-4f37-b890-903fb9586104",
   "metadata": {},
   "source": [
    "---------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5034e499-8e57-4970-a464-c1ea0ea48d80",
   "metadata": {},
   "source": [
    "## Data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "eb70f948-d2d5-455d-b817-70c5f0f6f32b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Cl1eO8frcgb6+BHjJLx7jLGIsAKnK3/d0KN/j3uKLSH63BxtfHW88pYKc7hpc1FvnFxap5oN6v7GI2QErb9fhVHOTnlq7Wo0tLa5jZqSl6fzCIo0pG6hzcrqr8fRp/Wt9lc/rT+yEjoizACD5hDJuVl1bo0VrVruN5eRn2zV3/CRV9CvV7qNHtPfI+zIsFg3qVayBRb3dYqdgE5aejiupSzzmLTZsb2/XG7u2aevB/TIMqfc556rsvCIVdO+u8sIiSdLLWzdpxc6tamptdT0uJzNTAwuLZVgs2lt3WI2tn8ZZ/mKosp6FIceACFzCJRDb2to0Z84cHThwQG+88YZrtpYk9erVS2fOnNHx48fdZm0dO3ZMF198satNfX19l+N+8MEHrllavXr10rp169zuP378uNra2rrM5OrIZrPJZrOFdH4AEE+qa2u0YPnSLrefaGrSguVLdeuUmW6JPjNf0s+sf0uv79gqwzA8PmdjS4seXvGqaj+s1+fHTgi6754GojwFPp76vPXQAY/B35gB5dqwf6/b7WZ1DIT8DWi9tGWjXt+xRa1tbUGfvyS1tLVpyZaNenX7Ft10yVTXa+V8/m0H92v5zm1dHud8fedPneUW7EYimYz4Eq9xFjEWgFTkLw4bXVKmTbU1Xu838z3uSbi+2x0Oh/bUHdbuo0dkMQxZrFa9tXtXlwGyssIivXvkPbfBJW+Wbt0ki6SOUaSn/no616yMDJX2/OR7pvaDY2o+4//5OjvT3q5dh9/TrsPveW3T8fpLInaCC3EWACQff/Fax3is81hQ4+nTenjFq10f2/zJYzPS0nSmvd11+yuS7DabxpcP0dp977pNcjI75lRdW6N/VK1Qc4e46xVJ6d26yWqxqLXD8zmld+umkh7naVblGA0qLNIjby7XpgP73Nrs/6Beq3fvkv7Tx7azZ9367tTY0qLNB/d7vJYdxxrrGo7rjR1b3eI1i8XiNpZoNgYk9gpNQiUQncHW3r17tWLFCp177rlu948ePVrp6elatmyZ5syZI0mqq6vTjh079D//8z+SpPHjx6uhoUHr16/X2LFjJUnr1q1TQ0ODKygbP368fv3rX6uurk5FRZ9kzF977TXZbDaNHj06WqcLAFHlaWbPorWrfT7mrytfk8MwlJudrW0H92tdzR6vAYz0SfJw2fYtpvqzbPsW9Tv3PI0pK/fZT09JSl8DZP5m7WfbbG6BlNOJpibTfffEGQhNHz6ySxLSuerSarXokVWvewyyQtF2tt2VlB1wXi9Tg4eStHhtlSr6lcpqtQYUFCMxEWcBQPSYKUvqLw7zlDzs6PGqFcrMsKn8vF5aur1aSzavN9U3MwNe/mZyV9fW6PGqFX6Tgieam7oMQPnTeQpa5/56i1lOnznjM/EXbo++udzjZDBip9REnAUA8SuYFWvOVXyPV63w2e7xqpWq6FfqcaK69zqHn/A0NtTU2qrXd2zpcruvMSfnOJgkjzGSJLWdPeu1H21nz2pvfZ32Ln3BT48/7WMoPCVVJXVZiGA2BiT2Co3F8LYEJAYaGxu1b98nfzxUVlbqvvvu05QpU3TOOeeouLhYn//857V582YtWbLEbebUOeeco4yMDEnS17/+dS1ZskSPPvqozjnnHH33u9/VRx99pE2bNqlbt26SpMsuu0xHjhzRggULJElf/epX1b9/f7344ouSpLNnz2rkyJEqLCzUvffeq48//lg33XSTrr76av3xj380fT4nT55UXl6eGhoa3GaWAUC86LgSrXPyz56ZqaYOP4di/tRZGt6nv7752F+8rjz05tbPzNTo0k9WzpmZSeQtYOhs+vCRISUEU8W3Lr9a5YVFunPxYz6TjgX2HP16zrykLQuRDN/pyRRnJcPrASA1ORwOj+WcOsczu+sO6/6Xn49RLz/h/G73VpnB20xus7FYuNltNn1lykz9bcWrIQ9cRUOyx06BSIbvdeIsAEhMwZSD9xTL+TK6tEybDvie+BUN2RkZau6whVCyKLDn6JfXfEk/efrxlB638ibU7/W4SiCuXLlSU6ZM6XL7jTfeqLvuukulpaUeH7dixQpNnjxZ0iebUX/ve9/TE088odOnT2vq1Kl66KGH3Oq3f/zxx7r99tv1wgufZM2vuuoqPfjgg8rPz3e1OXTokL7xjW/ojTfeUFZWlq677jr97ne/C6isA0EXgHhmtoxVOBTYc/SZoSP0zIa3g3r87FFjdbq1xWO5Taf5U2epol+p30SXU+fSB/Ds5snTlZttNzWI+a3Lr9ag/9TNd/JVsz4nK1sWw9CpltNxX5c+Gb7TkynOSobXA0Dq8VQyqjPnzOgNNXu0cOWyKPbOsytHjdGLmzd4vb/zTG6Hw6E7Fz3mVqYU3nmKnaTw7d0T7N5B0ZYM3+vEWQCQePxNevJUDt5fLIfY+PyYi02NOTpjr1TaJzGpEojJhqALQDzp+OVYf7LBdBmrcKnoX6qtBw9E7PgF9hzdOOkz+oPJkgow51uXX62TzU2mBjFvnjxdY8oGun72lKT2lbiN57r0fKfHF14PAPEgkIEHs6vynDOj99bXxXwFouS9tLuT3Zape6/7suu842HlZCLpHDtJ4du7x0wcFi+xF9/r8YXXA0AqcDgcpiot3XDJVDWebtbRhhN6qdr7pCrEVuf9Ir2ZesEInd+rOKX2SQz1ez2h9kAEAAQnmqsNvclMS4/o8Y83NWr30SMRfY5UU2DPUXlhkfbW15lqn5ttd/2/t4FSX/OWqEsPAEgUgSR5zOxn6HS8qVF76+tUXlikfLs9prGbJL8z7JtaW/TK1o26ovKT/dhOsvIwIMdOnnD7OVx795iNw4i9AACpam99nd8463hTox545d9R6hFCYSZ5KEnLd27zWN2MmMi75FyXCQBwcQ4gxHoAqvc55/rdIDpUFhbVh9U1YyfIarW6BjF9cSYbpcAGSj1ZvLZKDocj6McDABBJ3mIr58BDda37HjdmBqg62nZwv6xWq+aOmxSW/gYrM93c5K83dm5zfW93nEwE/1a/u8t17czET2ZipGDiMGIvAECqYdITPCEm6ooEIgAksVATOU6hJv4sFoue3bBGkU7vnd+r2G+iC+blZGVJkqlBzDnjJrrKlwU6UNqZc/UFAADxJpgkT6ADVOtq9sjhcKiypEy3TpkpiyXSU7A8a2lrM9WuqbXV9b1dXlikfJKIpp1obnJdO7MrIfzFSMHEYcReAIBUE81JT7GJ5BAMYqKuSCACQBJyOBzaXXdYSzavD8vKw8tGXhjS46O13e7fVy/XmAHlUXmuVNBxwLOypEzzp87qkqAtsOd0KfEQjpl8zAYEAMQjs0meN3YFvyqvsaXFNXAxesD5umXKjOA6G0XO722r1aq542O7cjLROK+d2djHX7tgYyhiLwBAKjFTaSlc0tPYRS6REBO5490LAEmmurZGi9as1okwfuEZ+mSj4XU1e9TY0hK244ZbQ3Ozlm3founDR2rD/r0xL9ua6DoPeFaWlKmiX6n21tfpZHOTumdmybBY1Hi6WbvrDqu8sEhWqzUsM/kogQYAiEdmBxSeXveWlm7dpC+Ov1SVJQMC3s+w4/OMLj1fdaOOa8nm9QH3N1o6fm9XlpRp9qixcd3feNI9M0u76w6r7vjHptr7i5GCjaGIvQAAqcRZacnTnsHhUmDP0YRBQ4mJEkzHmMjhcLjGwHKz7a5xr1RCAhEAkohzT55we2XLRtf/222ZGljUWw7HWW09VBv25wqHjfv36VfXXK+aD+p1oqlRp1pOq3tmlk61nNbT696KdfcSQsc9DTuyWq0aVNRb1bU1enT1crfB0Hy7XXPHTVJFv9KAB0rNPDcAALEWSJKlsaVFD694VdOHjwx4gKrz8xTm5pl+bCx8eOqkJLkGVWYNr9SKnVvV1Noa457FN7stU4+8+boamptNtTcTIzlXVAQShxF7AQBSkbPS0qK1q8M+Ad1uy9TnxlysIyfMTRBCfOgYE1XX1nR5bzjHvTpW4Up2JBABIEk4HA49XrUi4s/T1Nqi6tqaiD9PKI43Narmg3oNKurtdrvD4dCLm9er1eSePqms456GnXlLVJ9oatKC5Us1f+qskGby+XpuAABiKZjkzLLtW3TrZ2bq1ikz9Y+qN/zuLegpmRPvq8P+sfoNSVJ+tl1jysq1Yf9ekocmNLUGVtnDTIwUzIoKYi8AQKryVGkpkMk93jS1tmjhytfC1EtEizMmMjPulSpJRCJEAEgSe+oOM1DTgacSY9UH95M8NGH68JFeAyGHw6FFa1f7fPzitVWq6Ffqcc9Ei8X79uGe9lMEACCeOJMzgfrH6je0aO2bfpOHknTN2AldkjmNLacDfs5YONHcpGXbt1BGPswCjZG87V3dOQ4j9gIA4NNKS2PKBmpw7766dvwlse4STCqw52j68JFdYh67LVN2m61L2/lTZ3mMkTrGRGbHvZz7nSc7ViACQJLYffRIrLsQVz5uatK7h9/TqZbTys22q/Tcnq7Z8fBt4/59+uyF4z3ORN9bX+d3UPB4U6P21td1mcmXm21XWc9C1XxQr5PNTcrJypbFMFyvUSrWkgcAJJ5gyl21tLWZSh5KUk5WltvPDodD/1pXFXA/kfguG3mhBhf3CSpG8heHEXsBAOCZM9b751sr1dgSWLUARNbwPv01qHcfdc/MUv5/qnZYrVZ99sLxXfYqlOR1/8LOMVLH+wIZ9+pc+SwZkUAEgCRhMYywHSszPd30IFe8em7D27HuQsLyFQh5WtnpibOdcyZfR74CLDaoBgAkgsqSMjkMQw+/8WrYj935u9bMIEYiKSssUk19Xay7kRCK8wsCHpjyF0ulwkAXAAChqiwpU0tbm/7+5vJYdwUdZGZkaNqwkV1u9zT2JH0a93iKj7zFRIGOeyU7EogAkCTKi/tIWzeF5VjRSh4mQ6IyWXkLhMzuwRTMXk1sUA0ASBSRXBXYcLpZG2r2uAY3km1w4tyc7iQQTQo0niKWAgDAt0AmLe+pez9i/WA8LHoCjY8iOe6ViEggAkCSGNSrWNk2m5rDtA9iWrduaj97NizH8qTAnqOzjrMETHEqN9vuMbAuLyxSvt3ucyVEwX/KSEjmg3M2qAYAJJJIrQq0SHp63Vuun/Oz7Zo0eGjYnyfdapUhqT0Ge7esr9kT9edMRB3jKTOIpQAA8C2QRJLD4dCWgwci1pehvftqc+3+iB0/WfXI6e72s78xJ7PxUcfj5GRlKz/brhM+JvEFGqclMhKIAJAkrFar5k2c4vGLMRiRTB5K0oRBQ7Vk8/qIPgeCU2DPUWPLad25+DGPgfXccZN8vs/mjJsoq9XqMzjvWG8+Jytbi9b436C6ol8p5UwBADHncDj07pHIzEjvXJD+RHOTXty8QXabTU0mJ4nZbZlqavW9X49D0tkYJA9hnjOeMsPhcOjxqhU+2xBLAQBS2ab9+/Twiq6l571NtNlbX6fTZ85EpC+29HSSh0Ea2Luv6//9JYQdDocWrfU/1uQwDP1rXZXbcbJtNp+PCyROS3QkEAEgiVSWlGnqBSO0fOe2WHfFpfOAV4E9R3PGTYx4ghLBG116vsc9nToG1vOnzuoSqDlf28qSMr+zvAJdLZtKG1QDAOKXp4GKaGg/az7ZN2XIMC3ZstFnG5KH8atjPGXWK1s3+k0wE0sBAFLVpgP79NeVr/ls03miTSRLyLdSiSso3f7z2jgcDm09dMDvysJsW6bfmP14U6PH8S/neJW3Mc1UqupAAhEAkszwviVxlUCUpFElA3Rebr7smVnKzcpSti1TBgNXcWv5zq0+71+8tkq/njPPbRVhx1IRZmZ5BVNqN9n2gAIAJBZvk2OiobW9TbNHXqiqve/4HAjJttl05MTHUewZwsVus+nWKTM1sKh3QDPaHQ6HXttWbartiabGYLsHAEBCqq6t8Zgg6qzzRBu7LTPsfbFYLDKMzvUmYNZZh0MPvPJv5WVn+12UsHhtla6+cFzIz5neLU13zJqpUy2n/e6ZmaxIIAJAkjEsllh3wU1Ta6vH0gx5WdnKTM9QS1tkSkIgeP4C2o6BtadZ7JHaFypVNqgGAMQfM5NjIu2spLvn3KC99XXadnC/xwljzV7iLsQ/5+z2QAel9tQdVmt7u6m2i9dVKSMtLaVmzQMAUleg8Ztz0nJ1bY3+4ac0eDBIHoZHQ3Oz3zbHmxp1quV0yM91orlJFqtVY8oGhnysREUCEQCSTONp/1+k8aAhQfoJz9498r7bykNJrtWIkRi4TKUNqgEA8SdSk2MCYTEMWa1WlRcW6ZFVy2LaF0TGn5e/oovLh+jc7t3VPTNL+R3in85VH5y3rdy13fTxm1paPO7zBABAMgo0fsvNtse04gTCa1/dYeVkZqqxxffe4P68e+T9lFx56EQCEQCSiMPh0AkTM3GAUL3SYW+lbJtNFsnv3juhSKUNqgEA8SceymiXF/eRFB/JTERGa1ubVuxyX1nqKc6y22wyFFxJeKnrPk8AACSjQOK3AnuOynoW6gdPPRq5DiGqthyqDctxXtmyUWv2vqO54yal5AQsokUASBLVtTW6c/Fjemb9W7HuClJMc2trxJKHBfYcZskDAGIu1mW07bZMDepVLCk+kpmIHk9xVlNra9DJQ+nTcvQAACSzQOK3OeMm6tXtmyM6MRrxo8Ceo1unzFS+3dx75ERTkxYsX6rq2poI9yz+sAIRAJIAJRaQLPKz7brpkqkpvUE1ACD+lBcWKd9uj9nKv+snTnZ9H8Y6mYnkQCIaAJDszMRvFotFt0yeoYp+pfrH6vDve4j4k5OZqV9e8yWlpaXJarUENJ6ailUcUudMASBJBbopNBDP5o6fpMG9+2pM2UANKuqdUkEZACB+Wa1WzR03KSbPPX34SLeV+OWFRbLbbDHpSyC6WazKJ9kZt0hEAwCSnZn47ZYpMzR6wPl6ZetGNZ9h9WEqaGxpUc0H9ZKkypIyzZ86y/RKxFSs4sCoHAAkuFD2wSkvLApzb4DgUKoUABDvvA0wZKanR/R5l23f4lYuyWq1asqQ4RF9znA4azg0cdAQfevyqzV5yLBYdwcdFNhz+DsAAJASvMVvzjGI0aXnq7q2Ri9u3hCjHsKbjLTIFc/sWImhsqRMd8+5QZdXjA74samAEqYAkOBC+eK6fNRYLVzxqhpbWsLYI8C8y0ZeqMHFfShVCgBICJUlZaroV6q99XU62dyk3Gy73n3/kF7Ztjmiz9uxXFJ1bY1W79kV0ecLlxW7tquo4FxtOLAv1l2JC9k2W0h7F4bLnHETibsAACnDU/zmHIOgqlf8mjv+EmVnZGjR2tVuCydyMrPU2HI6pGN3rsRgtVo1qHdfvbx1U8CPTXYkEAEgwQX7xVVgz9GgXsW6qGyglu/cFuZeAf4V2HN0ZeWYsAxgORwOj38MAAAQblarVYOKert+dhhGxBOIznJJza0tCbXvdVNrqx5+49VYdyPm8rPtmjv+kxJqsXz9Cuw5mjNuolvFB2IoAEAq6By/OYVS1QuRdfpMqyYMHNIl+VvWs1Df+edCtba3B3Vcb5UYzOyZmYpVHEggAkCCM/MF54lz5vGI/gNIICImwjX7vbq2psuMtHy7XXPHTaIkKgAg4ppb/VdysNsyldbNqobm5qCfZ8XObar9z34tSByjS8t08+QZrphn/tRZXeKWSJs8ZJgqS8/vkhwkhgIApLpolaNM79ZNbWfPRuW5ksWm/fvkcDiUl21Xvj1Ho0vPd8Ux00eM0pLN64M6rrexKOeemb4me6ViFQcSiACQILzNDjbzBdeZ3Zapin6lkqSynoWyWCwyDCNSXQ+L2ZUXqjD/HP1txWuK754mJ7stU9dPnCxJerxqhZpCKL/VcfZ7qLPeq2trPL73TzQ1acHypeyrCACIGIfDod1Hj+iJt1b6bXvdxZfKarWEtPpsy8H9QT8WsbPpQI3OyVmjz4+dIMm9jNqW2v1asSvwiXx2W6YMGabLoVaWnt9l1QUxFAAA0StHSfIwcAc+qNeBDpPnOk5yurxitN7YuTWg0vCeKjF05twzs/MEKzOPDVa8V4MggQgACcDf7GBvX3DeNLW2aG99nQYV9VbNB/VxkzxM79ZNFotFZzqUIej4Jb3pwD6ShzE0vE9/Wa1WPdXtzaAeb7fZdOuUmRpY1Nu1h5OZWe/egikzexV03DMKAIBw8fQd5ktOVpYGFfXW/KmzQp6Ig8SzbPsWdc/Mcs2gLy8sUlnPQj38hvmE8pWjxui83HxXLFR9cL+eeGul3/eSp1JbxFAAAHwi2KpeiD7nJKdbp8xUTlaWxp8/yHRFtZzMTP3ymi8pLe3TdJi3sSZfe2aGWyJUgyCBCABxzuzsYOcX3JLN601t+rv5wD6999EH+uBkQyS6HRS7LVO/+sL1qvmgXieaGnWq5bS6Z2Yp25ap9vZ2/WP1G7HuYspqam3RDxb9XZ8ZOjzo8mvXT5yiwb37SjL/vvYVTGXbMv0G+c49ozztdQAAQDC8fYf54iyP5YzX7l3yrNuMaiS/Zzescf1/ts0mh8OhlrY2v4/LTM/QjZd8xm0Qqbq2xvTekp5KbZnZ74kYCgCQCoKp6oXY+uvK19wWQlgkv4sNGltaVPNBvSuu8Ze487ZnZjglSjUIEogAEMcCnR1stVo1qHdfUwnEVe/sCFc3w+ZEc5NqPqhXc2uLntu4xu2LnHrxsdfU0qIXN28I+HGdSz2YfV87DMPj4JgzmJp6wQhTzx+tPQ0AAMnPzHeYJx3LYz23cQ3JwxQXSLmtlrYzbj+bfQ/6KrVlNjYihgIApIKKfqXKttkC+n5G7HSuoma2UpkzromHxF0iVYMggQgAcSyY2cGJXn5h28H9HksQkDxMPJ1LljqZfV8/8fYqn23W1ewx1Y9o7WkAAEh+Zr7DOrPbMuUwDG2o2aPszCy9vmNrhHqHZNVxAMnse/CGS6ZqSHEfj/eZjY2IoQAAqWBvfR3JwxSQm22Pm8RdIlWDIIEIAHEsmNnBiV5+Ya3JpBDiX1Nrqyz/WRnb0YmmRnOPb2nxeX9jS4tyMjPV6KOdp31/AAAIltnvsI6aWlv0wCv/jkBvkCo6DiCZ/fug8bR7yfmO+/zkZGUrP9uuEz6ORQwFAEgVwcR3SCw5mVk60dSoN3Zti4vEXSJVgyCBCABxLNjZwZUlZbp1ykw9uWaVz+RKPPKXNEJi6RzsVNfWaPG6qrAd/6KygT43zfa07w8AAME6GeQ+wECoth3cr0FFvYP6+8DTPj/ZNpvPxxNDAQBSxamW07HuAiKsseW0Hln1uun2kU7cJVI1CKJBAIhjznKkvniaHVxdW6N/ra9KuOQhEsf48sGm2nUevFqwfGlYk8Qj+g/Q/KmzunxOCuw5cbPhNAAgeTSdobwVYmP5zm2qrq1Ro4lBzo5/Hzjjr86z7Z2l2uydEonEUACAVNM9MyvWXUCciXTiLtjx3lhgBSIAxDEz5Ug7zw72thkwEC4F9hx9cdwkrdn7rs92FotFZT0LJZnbIDqYfpQXFslqtaqiX6mrLFdutt11OwAA4cQ3C2Jp0RpzsdTFA4do04F9ysnK9vuY9G5pumPWTJ1qOU0MBQBISfn2nFh3AWFgkWSE4TjRSNwFM94bKyQQASDOVZaUaf7UWV3KDhXYczRn3ES32cGRSNIAnV044Hwd+OgDv+0Mw9Cr2zfrisqxpjaIlqSsjAydPnPGVD86BlNWqzXmG0sDAJJfeXEfaeumWHcDKcrXnoUdvVS9IaBjWqxWjSkbGGy3AABIaOWFRbKlp6u1rS3WXUEIwpE8lKKXuAtkvDeWSCACQAKoLCnzucLK4XBob32ddh9+z1SSBgjFsu1b5HA4TLV9cfMGFRecq/azZ021HzugXKve3em33dQLRsRNMAUASB2DehUr22ZzlX8EwsWWlq7W9tgMXEZ6nx8AAOKZw+EgeYiYJO78jffGAxKIAJAgvK2wqq6t6TJbBYi0dTV7TLddvLZKN076jKm2PfPyTbUryOmuDTV74jK4AgAkL6vVqnkTp1AuHmGVk5mpr1w6Xf/76osxef664x9rd91hYioAQEr659srY90FBGHK0BFav3+Pmlpagj7GNRdNUF5WdkzHluK9ohYJRABIUA6HQy9v3aQlm9fHuitIQY0tLcrJzFSjiUDteFOjDItF+Xa7z0R3gT1HkwcP0+s7tvhsZ7FY9PS6t1w/59vtmjtuEisSAQBAQmpsaZHFavUbK+Vn2yWZL2Vq1stbN+nlrZuIqQAAKcfhcGjT/ppYdwMBsFgsumXyDOVkZWnFrm1BH6fAnqPPDB3B5Ck/uDoAkICqa2v0o0V/J3mImLoogL1yGk83a+64ST7bzBk3UWlpaX7bGYZ7ZfsTTU1asHypqmsJ+gEAkcV+04iUxtPN+sLYiT7bzB0/SXPH+46TQkFMBQBINXvr63TmbHusu4EA3DJlhkYPOD/kEuzR2usw0XGFACDBVNfWaMHypWpobo51V5DiRvQfoNmjxppqm5ttd20QnW+3u91XYM/RrVNmKtuWqQ01e5Rty9StU2Z2aWexWHw+x+K1Vab3ZgQAIBh76+soG4+IOHbyhP61vsrjfQX2HM2fOkuVJWVe46lwIqYCAKSKE02NYT/m2LKBmjVilHyPYCAYs0eN1ejS8yV9Ms4UjI5xFfyjhCkAJBBmvSNeFNhzVF5YpPLCIq1+d4fPhLazreR5g+jGltP617oqtwHZfLtdX7hoonIys3SyuUkNp5vdypZ6crypUXvr6+K6djwAILEdP3Uq1l1AArDbbBpU1Fuba/ebbJ+pFzdv8Hr/58Zc7JpolZttV0W/Urd4qntmlh5583Wf8Vh+tl03XTJVu48e0StbNvrsDzEVACAVVNfWaPE6z5N3QjG8b39ZrVYZ/psiAPnZdl1eMdr1c3lhkd/y7544DCZJBYIViACQQJj1jnhxzdgJslqtslqtunb8JT7bXjjgfLeyEM4NoseUDVRza4sefuPVLu/rE01NeviNV9Xc2qIxZQOVl5Vtql+hlrAAAMCb6toaPbX2zVh3Awlg0uBh6n3OuabbG36GGP+2apnuf/l5LVz5yX/vXPyYth464IqnBvfu6zcemzt+kgb37qvi/AJTfSKmAgAkM2d1r6aWlrAfOzs9Q/9Y/UbYj5vqLhxQ3mVsyd8WOJ40NDdTsj0AJBABIIFE6g/59G7dInJcJK9/ra9yBVuVJWWaPnyk17bLtm/xGJiZWVHrLKFltjRFsCUsAADwxTnI1NLWFuuuIAEcPXHc54pCJ4ukKyrHqLm11Wc7M/s/+yoV37FMV/fMLFPnYLYdAACJJtLVvf647CVixgh4fUfXsaXKkjLTW+t0Rsl2c0ggAkACiVRypO3s2YgcF8mr48CVw+HQhv17fbb3FJiZWVHrLKHlLE3hS8dSqQAAhAsl5BGodw4fMtXOkNRyxnfy0JfO8VVlSZnunnOD7ph1lS4beaEurxitGy6Zqop+pZ8+p589pQNtBwBAoqG6V+LyNLZ0ecVoZaVnBHws53gTfGMPRABIIMHW9wYiZfHaKmWlZ5hOBHbcS8fsitqTzU2u0hQLli/12m7OuIlu5SwAAAgHBpkQqNb2dtNt19XsCfp5PMVXWw8d0KK1qz99z27dpHy7XXPHTVJlSZkaT3vfJ7Ejs+0AAIh3DofDtW9wbrZdJ5oaY90lBMlT7GO1WjWyZIDW7H034ONRst0/EogAkEDMJFGAaDre1KjdR4+Yats5MDO7ovbYyROSPi3N5TYopk9WHs4ZN9FVmgsAgHBiYAGR1NjSopzMTDUGuQdTx/ens9RuZ87KEfOnzqIsPAAgpVTX1nQZQ7BnZsawRwiVp9j8ZJATn4h3/COBCAAJxlsSJdZyMrN0fmEvbTl4INZdQZRZOu3L403nwKy8sEj52Xad8DMwu/rdXbqs4kJZrVZVlpSpol+p2+zB8sIiVh4CAMKi4wz1nKxsWQxDdcc/jnW3kOQuKhuo5Tu3BfVYZ3xldm/pX17zJb8VTSgLDwBIBt4m1jQFOWkH8aHz2NKmA/u0831z5eM7It4xhwQiACSgypIyDe/TX996/K8x379wVMkA7a47osaW0yQPU1R5cR/l73s34IEoq9WqiYMv0JLN630e/0Rzk1uJCqvV6lauAgCAcPA0Qx2IhuF9S7Rm3241twa2H2LH+Mrs3tI1H9RTFh4AkPTYwzo5Fdhz5DAMbajZo9xsu8p6FuqJt1cFdSziHXNIIAJAgnrkzddjnjy02zK1uXZ/TPuA2GtubdEXxk7Uwyte9drGW2BWmJtn6jkoHwcAiCRvM9SBSLPbMmVYLAEnDyX3+CqQvaXHlA2kLDwAIKmxh3Vyam1v0wOv/Nv1sz0zM+AVpcQ7gSGBCAAJqL29XZsO1MS6G2o/2x7rLiAOPPHWKqV18zxry19gxj48AIBYY4Y6Yi3QiVJ2W6aunzjZLb4KNKaiLDwAIJkxCTk5dZ5wFUjy8LKRF2pwcR/inQBxpQAgAa18d0dMn7/AnqPZIy9UazsJREhNrS1qaPa8YfU1F03wOaurvLBI+XbfA17+6tI7HA7trjusDTV7tLvusBwOh7mOAwAgZqgjtppaW3TSSxzl6zGdBRpTddzvk+QhACDZMAkZHWVlZOiKitEaVNSbeCdArEAEgAT04cmGqD5fRrduGnf+YJUW9tI5Od1V1rNQj1WtiGofkJieXveWKvsP8BqgWa3WkPbh8bRfVb7drrnjJlGOAgBgCjPUEWvPbVijzPQMtbSdMf2YxWurVNGv1BUjBRJTET8BAJKdc2KNr0liFotFhmFEsVeIldNnzugnTz9OrBME0q0AkIB6mNw3LlxmVIzWdRMna3z5YDW3tugnTz+u9TV7otoHJKbjTY3aW1/ns01lSZnmT53VZdZ8gT1H86fO8hrcOfer6vwHwYmmJi1YvlTVtbEv8wsAiH/MUEesOWQElDyUPMdYZmIq4icAQCpwTqzxZRSJpJTiK9ahspV3rEAEgAQ0efAwPbP+7ajNlCr8T8LSOeCA1FBgz1Fr2xk1nwlsQKszMys7At2Hx8x+VZ1n5gMA4ImZGepAPPIUY/mKqYifAACpxDmxpvOqe6dNB/Yp22aTRVJTp731kHhyMjPVaGJPxM6xDpUZfCMiBIAElJaWpmnDKqL2fLnZdlMDDkgOdptNd8y6SjdcMjXk5KFkfmWH1WrVoKLeGlM20G9dejP7VZlZ/QgAgJkZ6kA0Zaanm2rnLcbyFlMRPwEAUk1lSZnunnODrhw1xuP9za2tampt1ZWjxuiCPv2i3DuES4E9R/fMvVHXXDTBb9uOsQ6VGfwjgQgACcjhcGhY3xKV9iyM+HMV2HNUXlhkasAByeH6iVM0uHdfNZ5uDvlYzvdPuJndr4p9rQAAZngr/QjEQktbm3IyM322CSbGIn4CAKQih8OhFbu2+2xTtfsd/ff0K3RZxego9Qrh5Nzn2exK0pPNTaYrM6R6OVNKmAJAgvG0tD6SnF/CDCSkhgtLy1wlGsKxJ5Tz/RNuZvvGvlYAALOcpR9f2bpRy3duUzOlrBBDF5UN1PKd27zeH0yMRfwEAEg11bU1evytlWryU9ryeFOj7l3yrA58UB+lniEcbGnpuunSqZKkOxc/ZnqsNDfbHlBlhkFFvUPua6IigQgACSSSexBmZWTodIdylQX2HM0ZNzGsySTEv331R+VwOGS1WkPaE6rz+8cfh8Nhev9Dydx+VZFa/QgASF5bDx3Qi5s3xLobgIb3LdH5vYq7TBz0FWP5i6eInwAAqSTQMTSSh4knrZtVDsPQw2+8avoxzlhn04F9ptqn+oIKEogAkCAivQdhz+55+tyY8TrVctrrgIPdZmNj6SR3ornJNbvKuSeU2YA7Mz1dEwYO0Yj+A/wmADsKZsNqM32L1OpHAEByYr9nxJNH3nxd146/RHfPucHUJCsz8RTxEwAgVRDXpYam1lY98faqgB7jjHWozGAOUSEAJIhI70F46KMP9MibryutWzdX8qgzI2LPjnjScXZVZUmZrqj0vNl4Zy1tbf8p+dYSUPLQ14bV/1q7WrvrDnusOe9tv6oCe47mT51levUjAABS5GMtpJ6hvfsG/diG5mYtWL5UWw8d0KCi3hpTNtBrjO4vnqqurXHdFkz85HA4tLvusDbU7PEalwEAEE+I61KHv/K0Tp1jncaW034fY7dlpnxlBlYgAkCCiMaSeedAxfyps1TRr9RttvPZs2fZCyhFHDt5wu3nXnn5AT1+8doqVfQr9ZtENDMjcPnObVq+c5vXFYnO/aoCKX8KAIAnqV6eCOG36/B7IR/DX1xlJp7qfIxA4qdgKkUAABBrxHXozGF8OgHK4XDoX2ur/D7GMFhKQQIRABJENJfMP161Uk91e1MNzc1Re07Ej+U7tumyigtdg0iBvvfMbjIdyIxA5wx6TzPjrVZrSm9oDQAIj1QvT4T45C+uMhNPeTqGmfjJ295RvuIyAADiAXFdasjJzDK1klByXzSRbcvUCRNJ5uYzrabGt5IZ0/MBIEGUFxZ1KTUUKU2tLSQPU1jzmVbtqTvs+rmsZ6FyMjMDOoaZ2X7BzAhcvLaKslkAgIgoLywK+PsOiAZfMZPZeCrQuMvsykbiMgBAPIrmGBpi54vjLwn4dV68tkonmhpNt0/11awkEAEgQVitVs0dNynW3UCKePPdHZI+mXn+k6cfV6PJmvJOZmb7BTMj0DmDHgCAcLNarbqobGBUnuvmyTNkt9mi8lxIfL5iJrPxVKBxVyArGwEAiDeMoSU3536GowecH/DrfLypUadMrlqUum7zk2pIIAJAAqksKdP8qbOYHY+I23X4PW06sE8Lli8NeOPxAnuOqU2mg50RmOqzvwAAkTOi/4CIHt+Wlq7Zo8ZqdGmZplxQEdHnQnLwF1eZiafMxmYdRWplIwAA0eIcQ2MlYvKYesEIfevyq/XrOfNcZdSDeZ27Z2Yp3+Tkqhc3b1B1bU1Q/U0GJBABIMFUlpTpCxdNjHU3kORa2tr0xNurgnrsnHETXfsn+hLsjED2MgAAREp5YVFEVwa2trdpyeb1+t4Tf5NhGMrOYBUifPMXV5mJp8zGZh1FamUjAADRVFlSprvn3KBvXX61vnzpNNmZkJ/QNtfuV3lhUZe4xvk6X3PRBFPHybfnaO548+NRqVy2nQQiACSgfHtOrLuAFNAUYNlSZwkJ5ywwMwKdKRbMDHoAAAJhROE5mlpb9VL1BrU7zkbh2ZCIAomrvMVTwcRmTpFa2QgAQLRZrVYNKuqti84fpIvLB8e6OwiBr/LpVqtVnxk6wnT84oyfMtMzQnreZJcW6w4AAALn/IM+0NKS/lhkkRGVYTMki8srRqswv0CnWk6re2aWsm2ZcjgcAc1yrywpU0W/Uu2tr9O2g/u1fOc2r22DmUEPAIBZe+vr1NzaGrXnO9PeLkmy22xqiuLzIn5V9C/VlCHDNbCod9Dx1MnmJuVm2z3O0DfLubJxwfKlXtsQlwEAEkl1bY2Wbd8S624gRL7Kpwcav1SWlOlMe7seWfV6SM+bzEggAkACMvOFGAhbWpoGnNdL7xx5PyzHQ+LLycxSo4lNpbt1s+q5jWvcktn5drvmjpsU0Gx354zAQUW9dX6vYi1au9rtmAX2HM0ZNzGoGfQAAJgVq4GBM+3tSrNa1Z6ipZHwqa0HD+jgh8cCjqWkT+OpcHHOzCcuAwAkOofDoUVrV8e6GwgDf+XTnfHL41UrukzQy/awVYHZKm+pWradBCIAJKjKkjLNHjVWSzavD/lYre3tJA/h5tpxE/X0hrd9rnK12zL14uYNXW4/0dSkBcuXBl0yK9wz6AEAMMvswMDsUWO1YufWsK0abDtLKdNkl5OZqbMOh06fOeO3baixVDgRlwEAksHe+rqwV/FC9AVSPt1TnN7c2tolxjJT5S2Vy7YT8QFAAru8YrTysrNj3Q0koe7Zn6wi9MVfudtQNpl2zqAfUzZQgwIs4QUAQLDM7vt2ecVo3XvdV3THrKt02cgLdXnFaFX2L41SL5GIvjRhsm6Y9JmAHhNKLBVOxGUAgESXquUnk42Z8ulmVpt2jLGcVd5Cfd5klZpnDQAJzuFwaHfdYW06sE/nFxbHujtIQtsO7neVfeg8kFpgz9HsUWP97hGVyptMAwASk5kBhAmDhmrTgX3aW1+ngUW99V+jL9LsUWO1h+88eDH1ghGqLCnzGlt5QywFAEB4pGr5yWQyffhIU5UZzKw27Rxj+Rr/ioeKELFECVMASDDVtTVd9iEBwm1dzR59fuwEr2WrNh3YZ+o4zPIDACQab/u+2W2ZMmS4lY937vubbctUU0tLLLqLBDCi/wDX/ztjqyWb1+vlrZv8PpZYCgCA0JkpU4n4tnH/Pn32wvF+VwKajZ06t6Nsu2ckEAEggVTX1mjB8qWx7gZSQGNLi/bW17nKVA0q6u12v9nZe8zyAwDEM4fD4XGQoPMAwrGTJ3zu+zv1ghEx6D0SgcViUVnPQrfbrFarBvXuayqBSCwFAEDonFUmGFNLXM5Vg53HpzoLZbzK0/hXqiOBCAAJwkwNbyCcOs/G6jjImpOVrfxsu074mNmVyptMAwDin6eqDs4VhZUlZa4BBIfDoTsXP+bzWOtq9kS6u0hQhmGo5oP6LoNR5YVFxFIAAERRZUmZpg8fqWXbt8S6KwiSc5zK2yRAydxqU2Is80ggAkCCMFPD2xtberpa29rC3CMku46zsTbt36cn16xSY4fybNk2m8/Hp/Im0wCA+OatqoNzRWHHvU7MxGCNLS3Kycx0+54EnDpOynIOeG07uF8tbWd8Po5YCgCA8HE4HNqwf2+su4EQ5GbbPU4CzMnM1EVlAzWi/wCVFxb5XW1KjGUeCUQASBAnmhqDelxOZpYaW06HuTdIdh1nYz2z/i2PM/SaW1slSXabTU3/+X/nY+eMm5jSm0wDAOKXmaoOi9dWqaJfqaxWq+l9VPqf21M7D78Xji4iyTgnZZndy9xuy9T1EycTSwEAEEahTMxH7NltmWpsOa2H33i1y32NLS1avnOblu/c5qoo4mlPc8arAkcCEQASxKkgk4ClPc/T9vcOhrk3SHYTBg3VpgP7VHfiuN/yHund0nTHrJk61XKaTaYBAHHPzOBRxz1WzO6jQvIQnthtNjkMQxtr9uivK5eZekx6t27KzLBpQ80eV2wlyWupLgAA4J/ZSWGIT4ZhaLGJrZ2cFUVunTJTd8+5gfgpRCQQASBBdM/MCupxJA8RjCWb15tue6K5SRarVWPKBkawRwAAhIfZwSNnOzP7qADeNLW26oFX/h3QY040N7k9xm6zydCn1R8k9/06AQCAf2YnhSE+NZ9plXxXf3fz15Wv6ZYpMzS69PzIdSoFkG4FgDjncDi0u+6w6k8cD/oYljD2B/Ak2BK7AABEm9nBI2c7q9WqueMmRbJLgE9Nra1uyUPp09n11bU1MeoVAACJxTkpDKnBMAw9/Mar2rR/X6y7ktBIIAJAHKuurdGdix/T/S8/r5e3bgr6OEYY+wR48uTbqwjKAAAJwczgUce9gCWpsqRM04ePlMXCtCzEl8Vrq+RwOGLdDQAA4h6TwlLTX1e+pk0HGK8KFglEAIhT1bU1WrB8KeWykBBa2tr08IpX9cz6t2LdFQAAvHI4HNpbX6e+5/Tw2e7CAee77Y9SXVujZdu3yDCYloX44tyvEwAA+FdZUqb5U2cpjX3wUoZzJSJVG4ITV5+UN998U1deeaWKi4tlsVj0/PPPu91vGIbuuusuFRcXKysrS5MnT9bOnTvd2rS2tuqb3/ymevToIbvdrquuukrvv/++W5vjx49r3rx5ysvLU15enubNm6cTJ064tTl06JCuvPJK2e129ejRQ7fffrvOnAmgyC4AhMDhcOjxqhWx7gYQsGXbtzCzK04RZwFIdR0rO/jbI3rj/n2uVV0Oh0OL1q6ORheBoJjd1xORQ5wFAImjol+p0rp1i3U3EGW+qjY4t4/aULNHu+sOU92hg7hKIDY1NamiokIPPvigx/v/53/+R/fdd58efPBBbdiwQb169dL06dN16tQpV5s77rhDzz33nJ566ilVVVWpsbFRs2fP1tmzZ11trrvuOm3ZskVLly7V0qVLtWXLFs2bN891/9mzZ3XFFVeoqalJVVVVeuqpp/TMM8/oO9/5TuROHgA6eGXrRjV12ufEk5H9B0ShN0Bgnnx7FcFWHCLOApDKAq3s0HFV1976OipCIK6Z3dcTkUOcBQDxrWOC6I1d29TS1hbrLiHKvFVt6DjJcOHKZbr/5ed15+LHWLH4HxYjTmuwWCwWPffcc7r66qslfTJbq7i4WHfccYd+8IMfSPpkdlZhYaF++9vfav78+WpoaFDPnj31j3/8Q3PnzpUkHTlyRH379tXLL7+smTNn6p133tHQoUO1du1aXXTRRZKktWvXavz48Xr33Xc1aNAgvfLKK5o9e7bee+89FRcXS5Keeuop3XTTTTp27Jhyc3NNncPJkyeVl5enhoYG048BAIfDoe8+8Tc1m0ggAvHqW5dfrUFFvWPdjbBJtu/0RI+zku31ABBZDodDdy5+LOAk4M2Tp2tM2UBtqNmjhSuXRah3QGgK7Dn69Zx5biV3E02yfa8TZwFAfKmurdGitauZEAZXfO/knGTozfyps1RZUhaNrkVMqN/rCRNhHjhwQEePHtWMGTNct9lsNl166aV6++23JUmbNm1SW1ubW5vi4mINGzbM1WbNmjXKy8tzBVuSNG7cOOXl5bm1GTZsmCvYkqSZM2eqtbVVmzZtiuh5AsDe+jqSh0h4lNJKLMRZAJJZsCsInau6WN2FeDZn3MSETh6mAuIsAIidQKtQILl1jOvNbFPgq+xpqkiLdQfMOnr0qCSpsLDQ7fbCwkIdPHjQ1SYjI0MFBQVd2jgff/ToUZ133nldjn/eeee5ten8PAUFBcrIyHC18aS1tVWtHQb9T548afb0AMCFxAuSAYOtiSXe4yxiLAChCCa2KrDnqLywSJJUXlgkW3q6Wil1hRix2zJlyHCbZFhgz9GccRMTflZ8KiDOAoDYcDgcerxqRay7gTjRMb6XzE0ydJY9TaYKW4FKmASik8VicfvZMIwut3XWuY2n9sG06ew3v/mNfv7zn/vsCwD4Q+IFia5zUIbEEa9xFjEWgFAEE1t1XNX13MY1JA8RMzmZmbpn7o2yWq3aW1+nk81Nys22q7ywiJWHCYY4CwCi65WtG9VEhS/8R+eqDWYnGab6Qo+EiTZ79eolSV1mTB07dsw1u6pXr146c+aMjh8/7rNNfX19l+N/8MEHbm06P8/x48fV1tbWZSZXRz/60Y/U0NDg+vfee+8FeJYA8Mks93w7SUQkLkppJZ54j7OIsQCEIpDYym6zafaosaroVypJam9v1+s7tkaye4BPjS0tqvmgXlarVYOKemtM2UANKupNrJVAiLMAIPocDoeW79wW624gDhTYczzuZWh2kmGqL/RImIiztLRUvXr10rJln25ef+bMGa1atUoXX3yxJGn06NFKT093a1NXV6cdO3a42owfP14NDQ1av369q826devU0NDg1mbHjh2qq6tztXnttddks9k0evRor3202WzKzc11+wcAgbJarRozoDzW3QAC5i0oQ/yL9ziLGAtAKKxWq+aOm+SzTUbaJ8V5mlpbtWTzet25+DFV19Zo5bs7ZBhGNLoJeJXqM98THXEWAETf3vo6t9LfSE2XV4zWr+fM8zhOZWaSIRW24qyEaWNjo/bt2+f6+cCBA9qyZYvOOecc9evXT3fccYfuvvtulZeXq7y8XHfffbeys7N13XXXSZLy8vJ088036zvf+Y7OPfdcnXPOOfrud7+r4cOHa9q0aZKkIUOGaNasWbr11lu1YMECSdJXv/pVzZ49W4MGDZIkzZgxQ0OHDtW8efN077336uOPP9Z3v/td3XrrrQRSACKuurZGy7ZviXU3gIDkZGbql9d8SWlpcRVaoAPiLACprLKkTPOnztKitavd9jqx2zLV1NqiM+3tbu1PNDVpwfKluqBP32h3Fegi1We+JwLiLACIL0y+gSQN6t3Xa9UG5yTDBcuXen08FbbiLIG4ceNGTZkyxfXzt7/9bUnSjTfeqEcffVTf//73dfr0aX3jG9/Q8ePHddFFF+m1115T9+7dXY+5//77lZaWpjlz5uj06dOaOnWqHn30UXXr1s3V5p///Kduv/12zZgxQ5J01VVX6cEHH3Td361bN7300kv6xje+oQkTJigrK0vXXXedfve730X6EgBIcQ6HQ4vWro51N4CAOctrpfLG0vGOOAtAqqssKVNFv1LXPnLdM7P0yJuv+3xMTf1Rn/cDgehmteqswxHQY5j5nhiIswAgvjD5JjkV5uar/uQJU20L7Dk6e/as/r1pnSyGofLiPhrUq9gtIehtkmGBPUdzxk2kwpYki0E9log5efKk8vLy1NDQwEwvAKbsrjus+19+PtbdAIJy2cgLVZxfoNxsu8oLi5Jqlhbf6fGF1wNAOJiNuyyS+KMZsXLrlJkaPeD8WHcjovhejy+8HgCSwaYD+/TwG6/GuhsIs5snT5fVatUTb69SU0uLz7a2tDS1dqoykm2zad7EKV0Sgw6HwzXJMNnGtEL9Xo+rFYgAkOoosYBE9sqWja7/z7fbNXfcJGZrAQDiltm4a1jf/tr+3sEI9wbw7F/rq2S1WoipkPCSeXAWQHxxOBz617qqWHcDEZCbbdegot6q7D9Ae+vrtO3gfq2t2eOWTHRuUdA5eShJza2tWrB8qeZPneUWW1mtVipqeUECEQDiiNkSC7NHjVXV7p1uy+uBeOLcO6pzUAYAQLwwG3dNG16pXvkFen3HVlHAB9FGTIVkUF1b06U8HBMOAUTK3vo6xsuSkN2W6Srr7kz4DSrqrc+PneC+RcEq31sUSNKiNatV0a+UiSwmcIUAII6UFxYp3+57MKvAnqPLK0br7jk36IrKMVHqGRCcxWur5Ahwrx8AAKLBbNxVXlikz4+doD/e8FV9fszF6tmdkn6IPmIqJKrq2hotWL60y2C+MzleXVsTo54BSFZU90otzmTimLKBslitajjd7PcxJ5qbtLe+Lgq9S3wkEAEgjlitVs0dN8lnmznjJspqtWrroQN6qXpDlHqGZJHRLbrFB443NRKUAQDiUiBxlyRtf/+gXqxerw9OnYxG9wA3xFRIRA6HQ4vWrvbZhuQ4gHAzW2UCiaWptcVvLBRI8phEszkkEAEgzlSWlGn+1FldZsQX2HNcpYscDoeeWvNmjHqIRHbmbLvKC4tDOsY1F03QzZOn6/KK0abaE5QBAOKVmbhLkjbt36cFy5fqjIe9VIBQXDbyQmIqJC0zZQRJjgMIt/LCIuWTRExKJ5oaJX0yQWV33WFtqNmj3XWHXRNRAkkek2g2hz0QASAOVZaUqaJfqddN5vfW16mh2f+SfMCTvfVHgn5sgT1Hnxk6QlarVbvrDuvlrZv8PoagDAAQz/zFXZsO7NNfV74W414iGRXYc3Rl5Rjtra8jpkJSMpv0JjkOIJysVqsmDr5ASzavj3VXEGanWk773Fe3ol+p8rPtOuHneyX/P/E+/COBCAAx5nA4PA5YOWt4e7Lt4P4o9xL4xIRBQ10Dqs69o3zNKnbuHQUAQLzxFoN1VF1bo4ffeDVGPUSyc5bIJaZCsjKb9CY5DiCcHA6HzlIaOSm98/4h7Tz8Xpfbnfvqzp86S3PHT9KC5Ut9Hmfu+Eld4n54RgIRAGLI16wZZ8ksT49ZvnNbtLoIuCnMzXP9v3PvKF+BWce9owAAiBdmYjAze3cBwbDbbLp+4hTXe42YCsmK5DiAaPMU4yF5eEoedrR4bZV+PWee5k+dpcerVqiptdXtfrstU9dPnOx1zBVdkUAEgBiprq3xOEjQcdZM5y80BrIQa51nBzv3juocoBfYczRn3ESCMgBA3DEbg5nZuwsIxi2fmaUhxX3cbiOmQjIiOQ4gmrzFeEgdzn11nVsU7Kk7rN1Hj8hiGCov7qNBvYr5zgkQCUQAiAEzicDFa6tU0a/U7YuNgSzEkrfZwf72jgIAIF4EEoOxJxciocCeo0G9ij3eR0yFZERyHEA0MOEeTs4Y3mq1anDvvhrcu2+Me5TYSCACQAyYSQQ6Z8103AeRgSzEkq/Zwb727PTFzP5TAACESyAxGHtyIRImDBrq8/5gY6pwIC5DpJAcBxBpTLiHEzF8eJFABIAYMJsI7NyOL0FEg8VikWEYrp8jNTs4mD1AAQAIRSAx2OjS82W32brsnQKYYZFkeLh9yeb1qtq9M+7iHeIyRFosk+MAkp/ZGO+isoFaV7Mnwr1BrLCvbviRQASAGDCbCOzczswm9ECobpt5pdKs1ojODg5mD1AAAEIVSAxmtVo15YIKLdm8PsK9QjLplZuvay++RAN6FuqJtau1du+7XdrEW7xDXAYASHRmY7xxA4do99HDjKslKfbVDT+uJgDEgDMR6IunWTPOTeiBSGo83axBRb01pmygBhX17hJ8ORwO7a47rA01e7S77rAcDkdAxze7/1SgxwUAwJ9AY7DLK0YrO8MWja4hSRw9eUI7Dx/ST5/5p8fkYUeL11apvb09pLgqVMRlAIBkYDbGG9SrmHG1JFRgzzE94SnUMa1UwwpEAIgBZyLQ00xfpznjJkqSdtcddlsJVtGvVLNHjdWKnVspqYWIONVy2ut94ShvFeweoAAAhMpsDNZx8kxF/1Kt8ZMIAjpatn2LqXbHmxr1g0V/V1NLi+u2aJcNJS4DACSDQGK8ypIyTR8+Uq/v2Oq2fQsS0zUXTdBnho4wtfKQku2BI4EIADFSWVKm+VNndfnicu43J0l3Ln7M7b5sm00WicQhIqp7ZpbH2/2Vt5o9aqxmDa9UzQf1PsufBrsHKAAA4eAvBnMOHngaYADCrWPyUIp+2VDiMgBAsggkxjM72QfxLy8r23TykJLtgSOBCAAxVFlSpop+pdpbX+eWcNl66IDHL7VmEoeIgnx7TpfbzJS3WrJ5fZd9ojzN5Ap2D1AAAMLFWwzmHHzwNsAARMvitVWq6Fca8X18iMsAAMnEX4xnZmwDicVMjGLmdX+8amVUYq9EQwIRAGLMarW6lQMimEEsZXRLU1nPwi63mylv5YmnmVzOvQl8Hc/THqAAAIRT5xjMiVgM8SBaZUOJywAAycZbjCcFP7aB2LBYLD7LzJqNUcy87k2tLXpl60ZdUTk24H4mM9KpABBnCGYQS2fOtusnTz+u6toat9tDLVu1eG2Va2Nq594EvnTefwoAgGghFkO8ONHUGPHnIC4DAKQSSnInln7n9vB5v9kYxezr/sbOba6xK3yCCBAA4gzBDGLNuWqwYxIx1LJVx5satafusOtn594E+Xb34xbYc6g7DwCIKWIxxIuTzc1ReR7iMgBAqqAkd2I5+OEHXu+bPnyk6RjF7Ove1NqqvfV1ptqmCkqYAkCcIZhBvOi4946Z8lb+/GXFq5o3cYorwPO3NwEAALEQL7FYmtWqdmZAp7SXt25Uj9zcqCTwiMsAAKkgHGMbiA8b9+/TZy8cbypWKS8skt1mU1Nrq9+22w7uj3gJ+URCJAgAccYZzACx5tx7RzJX3sqf5tbWLisbnXsTjCkbqEFFvRmkAgDEXLzEYiQPk0uBPUezRwW2p87pM2e6xE6RRFwGAEh24RjbQHzoOGblj9Vq1ZQLKky1Xb5zW9Rir0RANAgAcYZgBvGkYxk3V3mrEFdm/POtVWpvbw+1awAAREQkY7H0bt0iclzEr8lDhulbl1+tX8+Zp8srRgeVnO64l7QkORwO7a47rA01e7S77jB79QAAEABvpbuReALZeuDyitHKttlMtX28aoXeOfI+MZZIIAJAXPIWzNhtmbJ3+rIrsOdo2rCRslgs0ewiUkTnMm6VJWW6e+4NunLUmKCP2dhyWj9Y9HdmdAEA4la4Js101nb2rLoRs6WUytLzXav5gk1Od5xhX11bozsXP6b7X35eC1cu0/0vP687Fz9GXAUAQAAqS8p095wbdEVl8GMbiL1Ath6wWq2aN3GKqbZNra164JV/E2OJPRABIG5524dEkvbUHdbuo0dkMQyVF/eR4XDo9R1bYtthJJQrKsdo5a5tPuu/F9hzXO+5jqxWq66oHKvignO1aO1qt70DLJIME8/f1NKiBcuXav7UWVHZ1wcAgEA5Y7FXtm7Ui5s3hO24Z41PvymtFoschplvTiQii8WixpbTbrc5k9OdYyh/TjY3qbq2RguWL+1y34mmJuIqAAACtPXQAb1UHb4YD9HlbczKl8qSMk29YISW79xmqj0xFglEAIhrzn1IOqqurXEfcNi6KQY9Q6JrOdPqd/PoOeMm+tz7xlOSu93h0B+XvmC6H4vXVqmiXyl77AAA4pLValVLW1vEjk/yMLkZhqGH33hV1qkWt0GnjjHUO4ff01IT8Xz3zCw9unq5zzbEVQAAmNPe3q6/v/lGrLuBEPgbs/JmRP8BphOITqkcY5FABIAE4m3WMRCot/a84/N+uy1Tw/v01+66w24rYDsHS52T3A6HQ/l2u+kZ9c6SXJ0T5QAAxINn1r+lZdu3xLobSHCL11YpM8OmxtPNys22q6xnoWo+qNfJ5iYNKu6jtXvf1Qkfe/gU2HNkWCx+4yviKgAA/KuurdGjby5XawQniSGyZo8aG/SKwPLCooDGraTUjrFIIAJADDkcji4lSr3NZnE4HFq0dnWUe4hk5W81RVNri36w6O9qamlx3ZZvt2vuuEk+gzTn3j6BJLoD2fQaAIBQmY2/2tvb9fqOrTHoIZLN8aZGPfDKv10/WywWGR1Wn2Z32uO8sznjJqrxdLOp5yKuAgDgU53jvsbTp/Xwildj3S2EID/brssrRgf9eKvVqjEDygOeJJiqMRYJRACIkS6lSOU7QbO3vi6g2TFAqDomDyXztd+de/v8862Vaux0DE8C2fQaAIBQBBJ/rXx3h1uSBwiXzu+r5v+UlbfbbG4l5gvsOZozbqIqS8q0u+6wqWMTVwEA8AlPcZ/FYolhjxAOQ3r3Denx1bU1QVUYSdUYiwQiAMSAt1KkvhI0J5oao9U9wCcztd8rS8o0vE//LqsYOwtm02sAAIIRaPz1zuFD0eweoPRuabpj1kydajndZXWsmXJbxFUAAHzCW9zH5LDEt2bvu3rnyHt+K2R5Emx1t1SOsVJv10cAiDEzX1aL11bJ4XC43Xaq5XQkuwWY5qz97k9aWpqunzDZZ5tgN70GACAQgcZfDodDNfVHo9E1wOVEc5MsVqvGlA3UoKLebjGSs0y8L8RVAACwBVAqcE4ArK6tCehxwVZ3S+UYKzXPGgBiyMyXlacETffMrEh2CwiI2drvznKm+Xb3Ug8F9hy/pVABAAiXQOOvvfV1fvcLBiLBV4xFXAUAgH9sAZQ6PC3A8CXQfQyJsShhCgBRZ/bLqnO7fHtOJLoDBCWQ2u+VJWWq6FfqtnF5x5JcAABEWqDxV6CDC0C4+IuxiKsAAPCNOC51OCcAlhcWmYqNzI5lXTbyQg0u7kOMJRKIABB1Zr+sOrczs+8JEA3B1H63Wq0aVNQ7Qj0CAMC3QOOvQCbKAJ2ld+um6cMr9fKWjQE9zmyMRVwFAIB3xHGpZdvB/Xpk1TK38dJ8u93jHolm95S+snJMyicOnbgKABBlzi8rXzwNHpjZ9wSIhgmDhmrTgX3aXXc4oFIRAADESqDxV3lhkew2WzS6hiR0Qe9+envvOwE/LpX31wEAIFzMxH1IHst3buuSEPS2RyJ7SgeOKwEAURbKl5Vz35OczMxIdQ9w6TxwardlKttm05LN67Vw5TLd//LzunPxYwFvWg0AQLQFGn9tPXRATa2t0egaklD37OygqobsP3Y0Ar0BACC1MAEfTp72SGRP6cBQwhQAYqCypEy3TpmpJ9esUmNLi+v2AnuO5oyb6PPLqrKkTC1tbfr7m8uj0dWUYJFkxLoTcSi9W5rumDVTp1pO69jJE3px84YubZyzugiyAADxzmz85XA4tGjt6lh1E0kg2Jnay7ZvUUnPQo0uPT+s/QEAIJU4HA5l2zI19YIRWlezxy3uQ2JJt3ZTm+Ns0I937pHYufQ7e0qbRwIRAGKgurZG/1pf5RbE2DMzdc1FE0wlYfbUvR/J7qUckoeenWhuksVq1ejS83Xn4sd8tl28tkoV/UoJtgAAccts/LW3vo49pxGSnnn5QT/2ybdXqbL/AGIq4D8cDgcDvABMq66t0aK1q4nlkkSb46xmjxqrqt07g35NTzZ7fhx7SptDAhEAoqy6tkYLli/tcntTS4sefuNVWadavCYRHQ6Hdh89ok3790W6m0gCV44ao7MOQy9v2Rj0MU42N5kaSPU2qwsAgHgQSPzlbZABMKPAnqPJg4fp9R3/P3v/Hh9Vfe+L/69Zucxk1pCLCiGJYEIIQW4xXIMEAYOSUvR0n2poVdy7x1rO6fm1R9vu7a6nZ599qXa3+3Hq7tl9PPah2G21aCXab91bqyiEiwQIICTclBAGghKGQFuSmJnMJGHN7w9c41zXrLVmzf31fDz6eJTJZ9Z8IjOs13wu70+XroGuYbebmYroM+EmAopFEesblrP6CRGFiJT3KL2VFhbh2ZZHsfPD43j94D7Nzy+08jzMWHDJDhFRAqkpiRWuPjdwIwg93foSfvbOv2P0uv7t+5Q9dp46gbV1C1CQn6/7GoVWUfVAKgdciYgoFWnNXxxkoFi0NDQiNzc3prOXmKmIPp8ICJ6Il49Q4DnsROSPJegzV6FVhCAIKCqwan5uiWhDTWlZHHqVPTiBSESUQFp2cvmL9OWJSInT48aWfbvxyLJVup4vBy21A6kccCUiolSkNX/VlJahWOQ9jbQpyM9H0+x5KMjLx0eXLmL8+o2SW8U68hEzFWW7WBbeElF2Ygn6zOQ/AagnH7U0NLLsdYxYwpSIKIH07OTiKiqKRcfZbhz7+DzumXsHDtnPYNDl8v0sV8jBuMJh1HLQkgdSlcI4V3UREVGq0pq/BEHA1JsnchCKNBkZHUXbqeNoO3U84PEiqxX3zV+ESYXFuDwwgN93HVa8DjMVkbaFHyz3S0QAd+9nKv8JwJrSMhRbRQyo+LsuEW1oaWhkuWsDcPqViCiB9Ozk4ioqitXI6Ci2n+jComk1EC0W3+NKk4f3zL3DF7QEQYhahuuBxcvQ0+/AYfsZdDv6uBqYiIhShtb89dtD+3D849449oiyyaDLhTePHkZuTg7uW7AY98y9Q7E9V8oT6Vt4S0TZjbv3M8+6+YsDJgCPfXweo9fHFZ9TX1mNtXUL8OhdTaibWhXvLmYF7kAkIkogPTu5+KWIjLLj5DHVbfef+QiFBVb88dMh3FJYhJUz52BjUzO2duwNeP+WiDYsnDYdrx1qD3i8WBSxvmE5V3sREVHSaclf4+Pjmu6XRGq1drTDkm/G1Jsn4ov1i9B2sgvusbGANlazOUm9I0otPEKBiLRSk/covQy6nNhxsgui2YIzjj4c6DkdsW1eTi4E040joDoB4NgRjksZhBOIREQJJO/k2tS2LWKb4FXH/FJEyeD0ePDbQ/t9f/7tof1YPacOz7Y8ip5+B4ZcThRaRQy7R7B557shzx9wOrGpbRs2NjUzrBERUVJpyV87PzwOr9ebwN5RtrjmHMbP3vl3xTYuj4f5iQj6Ft4SUXZTk/covew9fUp127EwOxM5LmUM1sUgIkqw+spqbGxqRrEYODFYItrC3tTkL09EyeT1erH9RBd+98EB1JZVYFH1DNSUluG1g+2Kz2vtaGc5UyIiSjq1+esPQ4PJ6B5RAOYnynZqjlBguV8iCqaU9+6eNTdJvaJkY66KDXcgEhElQX1lNeqmVgXs5KopLQv7BYirqCiV7Dh5DP9p/hLk5uaqOp/zmnMYPf0O1JZVJKiHRERE4anJX7cUFiWxh0Q3MD8RfT4REO4IhZaGRu4mIaKwIuW9nn4Hdn54ItndoyRgrooNJxCJiJJEEATVN6/6ymo0zZ6HtlPH49wrImVerxe7T5/E6jl3qD6fk+d4EhFRqoiWv1bOnIPfHtrPMqaUdMxPRNoW3hIRycLlPZ6RmN2Yq/TjHZeIKE3Mu21asrtABODz8m5qz+fkOZ5ERJQucnNzsXpOXbK7QcT8RPQZeSJgUfUM1JZVcPKQiHRRUxqZMhdzlX7cgUhElCIkSVJcWVlTWgZzXh48Y2NJ7CXR5+Xd1KzgKxFtqCktS1TXiIiINAvOYH+2cCn+NDyMI+fPJrtrlKWYn4iIiIwRnPMeX7UGrx1q507ELMJcFRtOIBIRpYDOXnvI2Q7Fooj1Dct9ZztIksTJQ0o6E4CykpshSZKq8zlbGhq5SpiIiFJWpAy2gGdrURIxPxEREcUuUs57cEkjbJYCHL9wjkcFZQHmqtjwvxwRUZJ19tqxqW1byOqnAacTm9q2obPXDgDYffpkMrpHWSI3J0dVOy+Af9n2H3i69SV09tpRX1mNjU3NKBYDy0GUiDZsbGr2TYATERGlGqUMxsEkMsq8qZWq2zI/ERERGUMp523e+S5cHjcebFiOdXcsTFIPKVYLqpTzkmi2MFcZgDsQiYiSSJIkbO3Yq9imtaMddVOrfOfOEcXD+PXrmtrLE9xyGKubWqVYgpeIiCiVqMlgRLEQzRbcOWMmtp/oUmx33/xFmFRYzPxERERkELVjbbPLp+DslcsJ6hUZpUS0oaWhEfWV1VgYZpepaDbj7tnz8IW6hcxVBuAEIhFREvX0O6LWXb/mHEZPv8N37hxRKpEnuAVBQG1ZRbK7Q0REpIqaDEYUi7ycHBw82x21XXv3R3imZQMHuIiIiAyidqzt27/enKAekRGs+WZ84+41mFFW4ctNXNAef/wvSUSUREMudQNXQy4nVs6cA5PJFOceEWkjT3ATERGlE7UZjEivAZcTQyMjUdsxSxERERmLOS8zuUY9sF9xhEwOygvaF1XPQK3f5CIZg/81iYiSqNAqRm/0Wbvc3FysnlMX5x4RacdwTkRE6UZtBiNKBGYpIiIi4zDnZa43jx5GZ6892d3IKpxAJCJKoprSMhSLysGmRLShprQMAPBnC5diQdV0cB8iGaEgP9+Q6zCcExFRulGTwaz55gT1hrIdsxQREZFx1OQ8Sl+tHe2QJCnZ3cganEAkIkoiQRCwvmG5YpuWhkYIgoDOXjuebn0JR86fhfezn+Xm5MS/k5SxWhqWRw3V0crm+k9wExERpQs1GYwrtigWJaINhQUFqtoxSxERERlHEAQsmlaT7G5QnLD8e2JxApGIKMnqK6uxsak5ZCKnRLRhY1Mz6iur0dlrx6a2bSGHQI9fv57IrlKGuck2IergabSyufIENxERUbqJlMFEswUA4PJ4ktEtyhAtDY346p0rVLVjliIiIjKOJEk4fK4n2d2gOGL598TJTXYHiIjoxgBW3dQq9PQ7MORyotAqoqa0DIIgQJIkbO3Ym+wuUoYRzWZIXi/qplZhY1MztnbsDZigLhFtaGloRH1lNaZNmqz4cyIionQVnMEmWArwwvs7kt0tSmPBGWljUzN+3b4rZEJaNFuwavY8jF+/jm5Hny/7ExERUWx6+h0hC/Aps0ywRK/yQMbgBCIRUYoQBAG1ZRUhjzP4UDw4PR787J1/R7EoYn3Dcjzb8mjYCWxAeYKbiIgo3flnsG5HHwZdriT3iNLN2roFKCu5KWxGknNU9+VL6Ll0EV6TCYLJhPbuU3jr6CFfOzmTcXEWERFRbLg7LfO98P4OfGXpXcxNCcCRPyKiFMfgQ/E04HRiU9s2HPv4PGrLKrCoegZqyypCJgflwdUFVdMBAEfOn0W3o48HVxMRUUZh7iI9aiumRMxQwGc5anI5aiumYHRsFL/vPBwyUS1nss5ee6K6TURElJEKrWL0RpTWBl0ubGrbhiPnzia7KxmPOxCJiFIcgw8lQmtHO+qmVinuKuzstYeUMuVqeSIiyiTMXaRH9cRSxZ+Hy1CRqMlkREREFFlNaRlsFguG3e5kd4Xi7Pnd7wEm+Ba7k/GYSImIUlxNaRmKRQ5mUXxdcw6jp98R8eedvXZsatsWMvDF1fJERJRJmLtID/vV/og/i5ShIomWyYiIiEiZIAj46tIVqtrOr6qGJTcvzj2iePF6vdi8812OScURJxCJiFKcIAhY37A82d2gLNAZoSypJEnY2rFX8bmtHe0sZ0pERGmPuYv0OH3pYtgcpCZDhcNSukRERLFZMG06Vs+5I2q7o+ft8Ho5lpHuOCYVP5xAJCJKA3VTq7Bu/mKYuSqKVGqaPQ8PLFmm6Tm7PzqJ595+A0+3vuRbvSVJEnZ+eDzqqnmulicionQkSRK6HX04bD/jW0RTX1mNjU3N3IlIqr3T9UFAfpL19DtU7zz0x1K6REREsZs7tVJVO8/16/HtCMUdx6Tih2cgEhGlOC1nphCZTCasnlOHLy9eBkmSsONkl+b3jlyW9J65d+DwuR7Vz+dqeSIiSifRzvatm1qFnn4HhlxODDid+O3h/UnsLaU6OT9tbGr2nQ2tJxuViDbUlJYZ3T0iIqKswzGK9FUi2vDA4mV4Zf9uOD0eVc/h33d8cAciEVEK03pmCpHX68X2E13o7LXHXIZt+wltk49cLU9EROlCzdm+giCgtqwCi6pn4NZbJiapp5Ru/Eto6clGLQ2NEAQO1RAREcWKYxTpx2o244t3LMKjdzXh3BWH6slDAJhgKYhjz7IXdyASEaUovWemEAE3Bq/qplYBuBHAXBpClx5cLU9EROlC7dm+dVOrfBM5wyOuRHSNMoBcQqu2rAI1pWUoFkXVC7JEs8WX34iIiCg21RNLYQLgTXZHSDWXx4Pfdx0GurQ/12syGd4f4g5EIqKUpffMFCLgxuDVO8c+wKa2bXGfPAS4Wp6IiNKHmowVfI7KlaGBOPeKUp1otmB+5TRVbeUSWlqrQTg9bp7fQ0REZJCz/Q5OHmYRLviLD470ERGlKNbuToyC/PxkdyFu3j3WGffXKBFtAWf9EBERpTq1GUtuJ0kS3j99Kp5dyljzqzInH0yfNBm5OeqKOPmXTKubWgWr2az6dfgdgIiIyBjdly8luwuUQCxZGx8sYUpEFANJktDT78CQy4lCq4ia0jLDdmHxxpcYkwqLcOEPV5PdjbgYvT4e1+s/sGQZ7p41jzsPiYgoJajNZWozltyup9+BQRdXNOtx9Lw92V0wzLFPelW1Cy7r3tPv0FQNgt8BiIiItAuXA01e7j/MFjxWJ344gUhEpFNnrx1bO/YGlMAqFkWsb1huyG4srWemkD6ZOnkYbyWijZOHRESUMrTkMjUZy38QgjvCSIvgsu5a3j8c/CIiItIuUg5snHF7EntFicRjdeKH/1WJiHTo7LVjU9u2kIGnAacTm9q2obM39tXWWs9MIdJj3fzFKBYDV7qXiDbcM/cOxecxnBERUarQmsvUZCz/+xx3hJEakcq6a3n/MF8RERFpo5QD3+r8AOZc7p/KBnNvvS3ZXchY/AQREWkkSRK2duxVbNPa0Y66qVUxDwDUV1ZjY1MztrTvglND6SMiNUpEG9bWLcDaugVhS75NmzQ5ZBVfiWhDS0MjzzwkIqKUoDeXyRkr0n2ubmoVuh19GHI5YSuwwma2YNjjjtvvQenrC3csxMzyWyOWzFWz49VkMuHrK+9lviIiItJATQ7MzcmFZzy+x7tQ8u0+fRKr59yR7G5kJE4gEhFp1NPviFpW9JpzGD39DtSWVcT8evWV1aibWoV3jn2AtlPHNZ2hQqTEf5V7uPeq/N6L1zmfREREsYoll0W6z3X2nsNf/eYFDLs/nzDM5+p1iqC8uEQx88s7Xje1bYvY5uur7sWCqunx6B4REVHGUpMDnVwAlhX+MDSY7C5kLH4LIiLSSO05JkaelyMIAr5YvxhfqFuInn4Hdp08hq6Pzxt2fcouWnYRCoJgyEQ4ERFRPMSay4Lvc789tA/bT3SFtBvlynWKQE2J0mg7XrnzkIiISDueU02yWwqLkt2FjMUJRCIijdSeYxKP83LkQS7J6+UEImkmms14fNUazCir4C5CIiLKCEbmsiPnz4adPCSKxGYpQPXEUlVtWdmBiIjIWDynOv3ddsskXPjDlZiuYTKZsHLmHIN6RMGYVImINJLPMVFSItpQU1oWtz7UTi5HXk5O3K5PmemRxlWYWTGFA1VERJQxjMplkiThlf17jOwaZYFh9wh+8PoWdPbaVbWXFwMuqp6BWi7oIiIiiomaHEipLdbJQwBYPacOuTxuIG6YVomINJLPMVHif7ZcPBz7+DzGrl+P2/Ups5hMJjy+ag3LYxERUcYxKpf19DvgdPOMHNJuwOnEprZtqicRiYiIyBhqciBlvmmTJie7CxmNE4hERDrI55gEr3QqEW3Y2NQc14kaSZKwtWNv3K5Pmefrq+7FgmnTk90NIiKiuDAil/EMHYpVa0c7JElKdjeIiIiySqQcSNmDGSy+uLeTiEinZJ1j0tPvwICTg1wUnclkwuo5dVhQxclDIiLKbLHmMp6hQ7G65hxGT78DtWUVye4KERFRVpFz4FtHD+HtY0eS3R1KMGaw+OIEIhFRDORzTBJFkiScvnQxYa9H6c3r9WL7iS5U3lIKW0FBQie6iYiIEi2WXFZTWoZiq4gB7kSkGAw4h9Ht6GPmIiIiSjBBEFBbMYUTiFmK1UTiJ62S7Pj4OH7wgx+gqqoKBQUFmDZtGv7+7/8+YIuq1+vF3/7t36K8vBwFBQVYuXIlTp06FXAdj8eDb33rW7jlllsgiiLuv/9+XLwYOCB/7do1bNiwAUVFRSgqKsKGDRswMDCQiF+TiCiszl47nm59Ce90fZDsrlCaeX73e3ju7Tfwy93b8dzbb+Dp1pd4Tg+FYM4iomwmCAIaZ85OdjcozbUebGfmorCYs4iI4q+mtIylTLMUq4nET1pNIP74xz/G//t//w8///nP8dFHH+EnP/kJ/umf/gn/8i//4mvzk5/8BD/96U/x85//HIcPH8bkyZNxzz334NNPP/W1eeKJJ/C73/0Or776Ktrb2zE8PIx169bh+vXrvjYPPfQQurq6sG3bNmzbtg1dXV3YsGFDQn9fIiJZZ68dm9q2sXQp6eL1egP+POB0YlPbNg5oUQDmLCLKZpIk4TrPTiEFYr45ahun2x3wZ2YukjFnERHFnyAIWN+wPNndoAQrEW2oKS1LdjcylskbPKqYwtatW4fS0lL88pe/9D325S9/GVarFb/+9a/h9XpRXl6OJ554Ak899RSAG6uzSktL8eMf/xgbN27E4OAgJk6ciF//+tdYv349AODSpUuYMmUK3n77baxZswYfffQRZs2ahY6ODixZsgQA0NHRgaVLl+L06dOora1V1d+hoSEUFRVhcHAQhYWFBv/XIKJsIUkSnm59iZOHZDibpQAPLlmG4s/CFktsRZYN9/R0ylnZ8PdBRInT2WvH1o69zFqkqLq0DPZ+h67nlog2PNOygVkrgmy4rzNnERElTmevHf+2ezvG/BZXUOba2NSM+srqZHcjZcV6X0+r9NrY2Ii2tjacOXMGAHDs2DG0t7dj7dq1AIDz58/j8uXLuPfee33PMZvNWLFiBfbv3w8AOHLkCMbGxgLalJeXY86cOb42Bw4cQFFRkS9sAUBDQwOKiop8bcLxeDwYGhoK+B8RUax6+h0c0KK4GHaP4IU9OwwrsSVJErodfThsP4NuR19ASSZKfamcs5ixiCheWOWB1Io0eWizFER97jXnMHoUJh+ZoTIfcxYRUeLUTa1CQX5+srtBBjHn5mFB1XQUB5UpLRFtnDxMgNxkd0CLp556CoODg5g5cyZycnJw/fp1PPPMM/jqV78KALh8+TIAoLS0NOB5paWluHDhgq9Nfn4+SkpKQtrIz798+TImTZoU8vqTJk3ytQnnRz/6Ef7u7/5O/y9IRFlBkiT09Dsw5HKi0CpG3fnFg4ApEeQSW3rDV7jdG8WiiPUNyxnm0kQq5yxmLCKKh/Hxcby8b3eyu0FpbnppGbounIvaLlKmZ4bKDsxZRETqaB0zC6en34GhkZE49ZASzTM+hiPnz6LIasV98xdhUmGx7vcGaZdWE4hbt27Fli1b8Morr2D27Nno6urCE088gfLycvz5n/+5r53JZAp4ntfrDXksWHCbcO2jXef73/8+vvOd7/j+PDQ0hClTpkT9vYgoe+gZIOBBwJRIrR3tqJtapSmEybs3gsU6KUmJlco5ixmLiIzW2WvHln27Q86sI9JKzeQhED7TM0NlD+YsIqLojFpUw4X4mWnQ5cKbRw9jY1Mzassqkt2drJFWU7R/+Zd/ib/+67/GV77yFcydOxcbNmzAk08+iR/96EcAgMmTJwNAyKqqK1eu+FZxTZ48GaOjo7h27Zpim/7+/pDXv3r1ashqMH9msxmFhYUB/yMikkUqkSUPEEQqH1lTWhayTZ8oXqKV2AomSRK2duxVbNPa0c5SXGkglXMWMxYRGUnOZJw8pEQp+ey8aX/MUNmFOYuISJneMbNwuBA/s/nnI5aBj7+0mkB0uVwhOyJycnJ8b4yqqipMnjwZ27dv9/18dHQUe/bswZ133gkAWLBgAfLy8gLaOBwOnDx50tdm6dKlGBwcxKFDh3xtDh48iMHBQV8bIiItYhkgEAQBjTNnx6trRCG0rNZTc0an1klJSg7mLCLKBmoyGZHRFk6bHnKPZYbKLsxZRESRGb2opqa0DKLZbETXKAXJ+aiz146nW1/Cc2+/gV/u3o7n3n4DT7e+pGmymaJLqxKm9913H5555hlMnToVs2fPRmdnJ37605/iv/yX/wLgRpmGJ554As8++yxqampQU1ODZ599FlarFQ899BAAoKioCI899hi++93v4uabb8ZNN92E733ve5g7dy5Wr14NALj99tvR3NyMxx9/HJs2bQIAfOMb38C6detQW1ubnF+eiNKalgGC2rKKkJrvEydwFSglzpWhAdVt1U42soRI6mPOIqJsoCaTERlt+4kuTJs0OaD8GjNUdmHOIiKKTOuYWTTHPj4Pp8djVPcoBR2/cA5tp46HPM4y8MZLqwnEf/mXf8H/+l//C9/85jdx5coVlJeXY+PGjfibv/kbX5u/+qu/wsjICL75zW/i2rVrWLJkCd577z1MmDDB1+a5555Dbm4uWlpaMDIygqamJvzqV79CTk6Or83LL7+Mb3/727j33nsBAPfffz9+/vOfJ+6XJaKMomWAIFzNd9FiiVfXiELsPf0hvlC3UNU5iGpLg7CESOpjziKibHBc5Xl1REYLPmeaGSq7MGcREUVm5KIaVpvIDh32M4o/D85dpJ/J6/V6k92JTDU0NISioiIMDg6yhjxRlut29OG5t9+I2u6++Yvw5tHD8e8QURRPrv2SqpV9kiTh6daXFFcLlog2PNOyIa2DG+/pqYV/H0Skh3y2DlGy+OerbMlQavC+nlr490FEiaZ2zEzNOIXaa1H6KsjPx8joaNR2ase1Ml2s9/XMTqFERAkW6fDemtIyFIvKq4dLRBveP30qEd0kikrtCkBBELC+Yblim5aGxowf+CIiouSKlMH8f87V6JRs/vmKGYqIiOgGtWNmNaVlUa/F0t+Zb9rEUlXt+F4wRlqVMCUiSmXhSo8WiyLWNyxHfWU11jcsV1z1vqx2Ft46eijiz4kSScs5iPWV1djY1Bzy/i8RbWhpaGTdeSIiiqtoGQzg2YeUGoLLkTJDERERfb6oRmnMTO2iGpb+znyFVqvKdnwvGIETiEREBohUEiv48N5IAwTLamdheMSVyC4TKdJyDiJwYwCsbmoVevodGHI5UWgVUVNaxlXzREQUV9Ey2Lr5i7G2bgFXIFPSmUwmVAetmJckCVazBX+2cCk+dY9ggqUAxZ/tsGCGIiKibKJ1UY0kSWHHH+TdjFw4lrk+vPgJiq0iBhTyvdodqxQdJxCJiGKkpiSWfHhv8CTLlaEBvH/6FHceUsoZcDnR0+/QVC9eEATWlyciooRRk8HeOnoIe0+fxF0zZyeoV0Theb1e2K/2+7KS0s5ZTh4SEVE2UrswOdYKYJTeBkdcWDd/seJYKsvAG4f/FYmIYqSmJNY15zB6+h0APp9kyc3JwZtHD2PQxZ2HlJreO34k7DlSREREqUBtWdJBlwtvHj0M0WxOQK+IIpN3wso7Z4Pfv/LO2c5eezK6R0RElHTymNmi6hmoLasIO3kY7R4q72a0WSyJ7DolUGlhETY2NYecnVki2nxV4MgY3IFIRBQjtSWx/NupWTFPlGynLn6CU5+Vhli/dDkDGBERpRTtZUlNcekHkVqdvXbYCqzYekBd9RKunCciIvqc1gpgo+PjeGHPjgT1jhKp0CqitqyCR+kkAP9rEhHFSO2hvP7t1K6YJ0oFAy6uhiciotSjNoPJnB431s1fzJ2IlDRHe8/hZ+/8u+KZPUBg9RIiIiK6QWsFsGLRlohuUYL5n28YbccqxY7/RYmIYiQf0Kwk+PBe7SvmiZJvS/tuljMlIqKUoSaDBZs4oRC5OTlx6hGRcfh9gYiIKJDae+OAcxjdjj4MOIdZxjQD8XzDxOJ/aSKiGAmCgPUNyxXbBN/ctK6YJ0oFTo8bZxx9ye4GERERAHUZLNin7hGeP01pgd8XiIiIAqm9N7YebMdzb7+BF/bswLDbHedeUaKIZgvPN0wCTiASERlAPqBZ7eG9elbME6WC7suXkt0FIiIiH18GUzGgVCLaMMFSkIBeEcUmuHoJERERqR9Lc3LSMOM01MzEPz30NU4eJkFusjtARJQp6iurVR/eK6+Y39S2LQk9JdLP5PUmuwtEREQB5Az2zrEP8ObRwxHbtTQ0wmpmGStKfSzNRUREFIpjadnJnJuLRxtXMRslCf+rExEZSMvhvfKKedFsTmAPiWJTU35rsrtAREQUQhAEfLF+cdSKEKwCQXrl5cR//XWk6iVERER0Q6QKYDZWmchYzEXJxR2IRERJ5vR4kt0FygILqqpxtt8R07lPotmC2snlBvaKiIjIWNEqQnDlOul118xZmFZahlf27wkojSaaLXB69JVKK7aK+Iu7mvCpe0SxegkRERF9LlzeG3AO44U9O5LdNYqDjrPdOO24iPUNyzmZmAScQCQiShJJkrC1Y2/Udl+8YxHcYx60nTqegF5ROssVBJjz8gImpUWzGatm12Ft3QIAwBlHH36x6124dExcP9K4koNaRESU8uSKEJHUTa2C1WzWdS+k7FUsToAkSXhsxT3ou/Yn/PHTQdxSWISVM+fg2Me9eH73e/BqLPW+fulyzKyYEqceExERZa7gvNft6EtibyjeBpxObGrbxkoNScAJRCKiJOnpd2DA6YzarmZyGX61ty0BPaJ0Ny5JEHNysKCqGh9dugiXxwOnx4O3jh5Ce/cprG9YDqvZonnAtNgqYv1SrvQiIqLM0NPv4OQhafbbQ/vCPr7jZBeW187SNHlYItrQ0tDIbEVERGQQuUy9mnE2Sl+tHe2om1rFxe0JxAlEIqIkGXKpCzXdly8xAJFqgy4Xjpy3hzwur9Zqmj1P1XXW1i1AWclNLKdFREQZR20GI1JjwOnEm0cPq2q78vY5qK+azmxFRERkMJapzw7XnMPo6XcoVhshY3ECkYgoSQqtYvRGAEwaSyERKTloP6OqXW3FFAYyIiLKSGozGJHR6qumM18RERERxWDAOZzsLmQVLnkjIkowSZLQ7ejDgHMYNotFsW2JaMP0yeUJ6hllg2G3O+r7TjRbUFNalqAeERERxZ+cvw7bz0DyelHMSURKMOYrIiKi+BkfH8fL+3YnuxuUAJ+6R5LdhazCHYhERAnU2WvH1o69qkuStjQ0wsTyRmSwJdUz0HbqeMSfOz1uHPv4PM/lISKijBAuf1nN5iT2iLIR8xUREVF8dPbasWXfbjjd7mR3hRJggqUg2V3IKhyVJiJKkM5eOza1bVM1eVgi2rCxqRn1ldUYHnEloHeUTWbfelvUgdPWjnZIkpSgHhEREcVHpPzl8ngAAOa8vGR0izJUtPcT8xUREZGx5KzHycPsUSzakt2FrMIdiERECSBJErZ27FVsY7NY8OCSRhSLNtSUlkH4bOchz+kho/Vd+6Nv4DQSHkxNRETpTk3+8oyNJag3lOlslgIMRympxXxFRERkHDVZjzJLyWdjppQ43IFIRJQAPf2OqDsPh91uFIs21JZV+CYPAaCmtAzFIicRyTh//HRIVbshl7pSu0RERKlITf4iMsqS6hpV7ZiviIiIjMGsl31aGhoDxkwp/vhfm4goAQacw6rahRtQEAQBi6apG5AgUuNmW6Gqdtz9SkRE6YwTNZQI8tED826bpqo9z+0hIiIyBrNedlk3fzHPkk4CljAlIoqzzl47Wg+2q2obbsKms9eO7Se6DO4VZSvRbMH2k51R29ksBRhwDqPb0RdQUpeIiChdcCEMxVNBfj5Wz6nDF+oWQhAESJKEYlGMuhPihfd34CtL7+IAGBERUYyY9bJHsVXE2roFye5GVuIEIhGRgSRJQk+/A0MuJwqtIoZHRrB517uqnhuujvf4+Dhe3rc7Dj2lbOX0qDtYfNg9ghf27AAAFIsi1jcs50AXERGlPP8sZiuwotgqYoCr0ykORkZH8ebRwygvuRn1ldUQBAHrG5ZjU9s2xecNulzY1LYNG5uama2IiIh0kiQJktcL0WyG0+NJdncozhZV13Bhe5JwApGIyCCdvXZs7dgbsOrYpOH5wXW8O3vt2LJvN5xudRM+RPEy4HQaMtAVPMHOnY1ERGSkzl47th7YGzBhaM03J7FHlA1aO9pRN7VKc6bR+zzmKSIiynbhxt8os31w7iz+bOFSQzMPM5U6nEAkIjJAZ6897Gpjr4rn2iwFeHjZioCJmUjXI0omvQNdQPiAz52NRERklEjZyTV6Y0W6JS8P7rGxRHeLssA15zB6+h2oKS3D1o69mp9XW1ah+jnMU0RElO04Xpad9OQmJcxU6nFKlYgoRpIkaRosCPbgkmUBN6dYr0cUL3Jg00oO+MGrA+WdjZ29dqO6SEREWUiSJGxp3xWljZplXUT6DLmc6Ol3aN4JMaShvC7zFBERZTs142Wi2Yxv3fNFTRXBKD1oyU1KmKm04QQiEVGM9AwW+CsWbYZejyietAY2NQG/taMdkiTF0i0iIspiZxx9Uc++Gb0+nqDeUDYqtIq6BrUKraKqdsxTRERE6sbLnB4PNu9+T1VFMEovanOTEmYq7TiBSEQUo1hWwJSINtSUlhl2PaJ40xrY1AR8vTsbiYiIAKD78iVV7Sx5eXHuCWUjOc9rzUjhvgdEwjxFRESkfryMZeszj5bcpISZSjtOIBIRxSiWFTALp00POU9ugqUg1i4R6WI1mxV/riewqQ34nDgnIiK9TF51a8wnF98U555QNmppaIQgCKgpLUOxqP57gfw8NZiniIiIjNmBRulpWe0s1blJCTOVdpxAJCKKUU1pGWwWi67nfnDubMi2+LP96lbRE2lhMpnw+Ko12NjUHDK4VSLa8PiqNbh7dp3iNbQMdMnUBnx+ESAiIr1qym9V1a73an+ce0LZpES0YWNTM+orqyFJEnr6HVjgd665muepxTxFREQEzYt1KHOUFhYZch1mKu1yk90BIqJ0JwgCvrp0BTbvelfzc+Vt8bVlFQBu1OLeeeqE0V0kgtfrha2gALVlFaibWoWefgeGXE4UWkUMu0fw2sH2iGUcSkQbWhoaNQ10yeSAr1QiwqhSFERElJ1qJ5fDajbDFeUcRCIjVE+ajJsnFKJhei1mlt+Kzl47tnbsDcg6JpMJXr+dsTaLBUuqZ2DebdNQU1qmeUEW8xQREaUjeYGNPPag5x7oTxAErG9Yjk1t2wzsJaUDoyb0mKm04wQiEZEBFkybjt4/9GP7iS7Nz/XfFt/T74BrlINfFB/ye00QBN+kdWevHZt3Rp78vm/+InyhbqHukK8m4OvZ2UhERCQTBAEbGldxMIkSwn7lMuxXLuOQ/QzMubnwjI+HtJEnD5tmz9M9aeiPeYqIiNJNuAU2xaKI9Q3LdS1OltVXVmNjUzNe3rcbw263EV2lFGfkhB4zlXb8L0FEZJAvL16Gx+9eA1FjOVP/VTSssU3xFLxiS5IkbO3Yq/ic9u6PYn5dOeCHK52qtYQXERFROPK9pshqDXi82Cqiafa8JPWKMl24yUN/R3vPxTx5KGOeIiKidNHZa8emtm0hu7wGnE5satuGzl57TNevr6zGg0saY7oGpY+F06YbOqHHTKUNdyASERloQdV01N82DT39Dgw4h9F6sB1OhRVRwatoWGOb4iXciq0b71PlSevgMrt61VdWh5RONWpAjYiICIh8r+npd6Dt1PFkd4+ykFE5SsY8RUREqU7NQuXWjnbUTa2K6f5VLNp0P5fSywfnzuLPFi41fBKRmUodTiASERnMvzxkfm6upm3xNaVlKLaKGOBORDJYuBIMane8GrUz1v+zQUREFA/h7jVqzjohihejK4wwTxERUSpL1EJl5rvscc05jJ0fHsfds+YZOsHHTKUOp1SJiOJI67Z4QRCwqLomkV2kDDJ3ym1h32uPr1oDq9mCw/Yz6Hb0QZIkAOp3vHJnLBERpTNBELBoGvMVJYecoyRJQrejLySPERERZZJELVRmvssurx/ch6dbX4q5/C1pxx2IRERxpmVbvCRJOHyuJwm9pExw4pMLePzuNbBZCjDkcmKCpQA9/Q68sn83nB6Pr518cLnk9Ua9ppGHVRMRESUD8xUli2i2oKa0DJ29dmzt2BuwS0LOYzxnh4iIMkmiFioz36W/grx8rK1fhN8e2qeqvXyGJs8pTCzuQCQiSgB5W/yi6hmoLauIuOVeTakHyjwlog3r5i/Gytvnxnyt1w/uQ01pGXJzcvCLXe/i952HAyYPgc9D1yv7dke93gOLl7EGPBERpTXmK4qFyWSK6fmdF85hU9u2kPegnMe4kp6IiDKJXFpUiRELlZnv0p/k9WLV7XOivl+CtXa0s5JDAnEHIhFRnEmSpPpQXqPPSKHUVzWxFFeGBvDW0UOGXO+acxjvHPsAbx49HLVt8MRiOLaCAiO6RURElDDB2WvAOZzsLlGamV85DfWV1Si0ihh2j2Dzznd1XcfpceOV/XsU27R2tKNuahUXbBERUUYQBAHrG5ZjU9u2iG1aGhpjvu9x/Cz9ecbH8M7xo1HfL8GMOEOT1OMEIhFRHIUrV2SzWPDVpSuwYNr0kPY8ay77nL/ab/g1204dN+xaDOVERJROwmUvS15eEntE6eho7zlf5RAAwCpg8y6dk4hut+LPOQhGRESZpr6yGhubmkMyWYloQ0tDoyHlJzl+lhl+33kYG5uab7xfDuzFQILO0CT1OIFIRBQnnb32sCtoht1ubN71Lnr/0I8vL14W8DO51APLMFAsXCp2FqqlJ5Rr2XVLRERklEjZyz02FvW5NksBht0j8egWpSn/nYHxrsgQPAjGLEVEROmuvrIadVOr4nY/4/hZ5mjtaMczLRtgyTfjZ+/8u6rnJGICmXnsBk4gElFWi9fNQJIkbO3Yq9hm+4kuTL15Egqt1oDX17p1n8ifaDarKk2qhv+5BGo/K+F2fhSLItY3LOch10RElNTspeSrS+/Ca4faOQhFPv47A/Wuclc7Me0/CMYsRUREmUIQhJh22CvlRjWlUik9yJlreMSlqr1oNsd8hmY0zGOf4wQiEWWteN4M1B7m/Mvd7wX8uVgU8eDiRqybvxi7Th0zbCKIsseq2XWGnacon0ug9rMSaefHgNOJTW3bsLGpOeuCFhERfS7W7KU0iKQ2ewUzmUxYPacOC6ZNhyCYOAhFAY5fOIfasgrdq9zVTEybTCbfJCOzFBER0Q1qcmN9ZTUeX7UGz+9+D16vN1ldJQMMuZzounBOVdtVs+viuhOQeSxQ9u25JCLC5zeD4C/z8s2gs9ce0/X1rlIecDqxede7eOvoIU4ekiY2SwE2NjVjbd0CFIuxlXIoEW2+QKT2s6Jm50drRzskSYqpb0RElJ5izV6dvXY83foSnnv7Dfxy93Y89/YbeLr1Jd/z9GYvr9eL7Se6fNexms26rkOZad+Z0xgfH/eVSdPCkpePuqmVWN+wXLGd1+vF5p3v4sj5s8xSRERE0JYbF0ybjq+vujfRXSSDiWYLjpyPPhZrzTdjbd2CuPWDY1uhOIFIRFknETcDHuZMiWSzWPCP6x/1rYBqrJ0d0/UevasJ9ZXVmj4ranZ+yGUpiIgou8SavdQMIsWavba078amtm2GniNM6c89NoqnXn0Rbx87ggUaV5q7x0bx1NYXAQCPr1oDk8mk2P43+/cwSxERUdbTkxsXVE3HxqZmmHNZbDEdmQB09JxW1bbutqq47j7k2FYoTiASUdZJxM2gprQMNrNF9/OJtHh42Urk5ub6dmdEKmGaK+Soup5cd17LZ0Xtzg+9O0SIiCh9xZK91A4iVU8sjWkHvtPj1v1cymxOjxtvHT2EtlPHASDqRGDAc91ubGrbhsuDf4paWm3Yre49yCxFRESZTG9urK+sxrr5i+PZNYoTL4BD53pUtY33JDHHtkJxApGIsk4ibgaCIGDFrLm6n0+khly2VKnUqOyL9YuQn6cuaMm7OLR8VtTu/ODuXCKi7BNL9lI7iGS/2h+1VCSREfScsbTzs8lHIzBLERFRJoslN666neNwme6WwqK4Xp9jW6E4gUhEWSdRN4PJRcUxPZ9IiSUv31e2VM3ujD0fnVBVls1mKUBNaRkAbZ8VNWcDlYg237WJiCh7xJK9tAwi1VdWY2NTc8xnAROpoWknosrSuDaLcgUTZikiIsp0seTG3NxczCirMLpLlCJMJhNWzpwT19fg2FYoTiASUdYx4mYgSRK6HX04bD+Dbkdf2DN7smk1CiXeshkzkftZ6QY1uzPUlsVaUl3jqyev5bMiCELUnR8tDY1xrVVPRESpKZbspTZPTbAUALhRvurZlkfx5NovoWn2PIhRJmSI9NK6E1E0mxV/XiLa8NWlKxTbMEsREVEm8h9jk7xeFEfJf+Fyo3yNpTUz49lVSqLVc+p842DxwrGtUDxZlIiyjnwz2NS2LWIbpZtBZ68dWzv2BkzYFIsi1jcsR31lte8xebAs2sQOkR7zbpvm+/9G1l73v67Wz4q88yP481Ei2tDS0Bjw+SAiouwRS/ZSm6deeH8HvrL0LtRXVkMQBNSWVaC2rAJfXrwMPf0OHL9wzneGHZFRmmbPw0H7GVULtVbNrot4TjUAX1YSBBOzFBERZY1wY2zWKItugnNjuGtQZllQNR1fXrwsIa/Fsa1AJq+eAv6kytDQEIqKijA4OIjCwsJkd4eIgoQLGNFuBvI5c5HI59GpbU8UTn5uLkbHxyP+3GYpwD+ufxSCIKCn34Huvk/w9rEjUa9rs1gUB7hKRBueadkQMoCr9bMiSRJ6+h2+sxHlHYrpjPf01MK/D6L0pCd7yc9Tm6eCs5i/3x7ahx0nj+k6w44yX15ODsauX9f0nLV1CzCttAzP73oX7rGxiO3kjHXs4/OqPgOZmKWU8L6eWvj3QUSJEi3jiWZzQBnwcPdMjrtlvqICK370lT83LAupzVmZksdiva9zAjGOGLqIwkulf4C19EWSJDzd+pLiiqZwEzBcCUXxYDWbYYL6M3VKRBseWLwMm3e9G7HNPXPviLiiK5U+t8nAe3pq4d8HUWSp/u+13v519tqx9cBeDETZda+0GIaDS5Qs/hPbqf4ZTQbe11ML/z6ICIj//UrNGFuxVcRf3NWET90jYfug5hqU/pQWCGqltqpcJon1vs4SpkSUUKn2D7Vc4koNNefMXXMOo6ffEXDN+spq1E2t+uz5w2g92A6nyvPoiCJxqZw4lMmr9Hr/0I/tJ7rCttl+ogvTJk0O+1nU8lkhIqLkSLWcFY7e+0l9ZTUs+Wb87J1/V2wXLotJkoStHXs1vyZRrMLtlGCmIiKiVJeITKlmjG3A5YRJELCoeobua1D6MrpkaKQFhQNOJza1bTN0ojKTZPcyNyJKKPkf6uCbu/wPdWevPUk9U0ftOXPh2skDBcWijZOHlFAlos0XgiRJwuFzPYrtWzvaIUlSgnpHRERGSfecpcbwiEtVu+AsxsEl0spmseBrK1bjvvmLUGS16r7GPzzwMAeiiIgorSQqU8Yyxqb1GpQ+5Az25Nov4ZmWDYblKDULCjkeFh53IBJRQoyPj+PlfbsV27R2tKNualXKlvAptIoxt2O4oUT5wh0LMbP81oASH3p30RIRUWpT84X45X17MPfW25Cbm75fAfVmMeYv0mrY7UaxaMOS6bX4Qt1C9PQ7cPrSRbzT9YGma9iv9jNTERFR2lA7yWLE2J0RY2xqr0GJlSMIuK5zIk7OYEbnJ46H6Zeao/RElFE6e+14auuLGI6y807+hzpV1ZSWoVhUDiclog01pWURf85wQ4lSXlyC2rKKgFBvxAo/JZIkodvRh8P2M+h29HHlFhFRgqj5QjzsHsFTW19M652IerMY8xfpIechuZJIeXGJ7msAzElERJT6tEyyxMqIMTY116DEWxDjrsF4LP5Te80B57Dhr53u0nf5KRGlhUj1pSNJ5RXigiBgfcNyxd+npaFRcRWWHG5YRoviLdxgqREr/CJJh3O3iIgyldr85HS70/p8D71ZjPmL9AjOQ3rykfwc5iQiIkoH8V507M+IMTY116DEWzLjdpzpv6Q7e8dj8Z/aa7YebEd+bi7zmR/uQCSiuFFT+iBYqq8Qr6+sxsam5pAVTv7nzCmRww1RPEVapWfECr9wsuHcLSKiVKY1P6Xz+R56shjzF2kVLg9p3eUgX4M5iYiI0sUES4Gh7aKJdYxN6RqUPO5Rj+7srWdMSg21OU5ecMl89jnuQCSiuFFT+sBfvG4SRquvrEbd1Cr09Dsw5HKi0CoGnDMnkyQpbBs53ASvQrbmm+Ea9ST616EMFGmVnhEr/IIl8owEIiIKT+sOu3Q/30NtFvNXN7UK6+Yvxq5Tx+D0fJ63RLMFTo9ymX3KPuHykNZdDi0NjQDAnERERGnDazIZ2k4NPbkuWN3UKuTn5WNz2ztwj40Z1jfS55V9e/BPD30t7NhntOy9rHYWjpw/q+t9oERrjmM++xwnEIkobrSWNNA6cZFM8lkokUQrUxQckCZYCvCLnSy5QLEpEW1oaWhUXKUXaQJbzXPD4UHURETJp6d8UyqXjVcjWhbzFy6XWc1mNM2eh1smFOGFPTvi1U1KAfk5uTCZTPCMhw4omkwmeL1e359LRBuW1c7C+PXr6Hb0hQxcRcpR/vwzVbejjzmJiIjSxvCIy9B2amnJdcHC5TxKLqfHjTOOvoiTw8c+Po+tB/ZiwBU4seiFF28dPeR7zOhy73KOe3nfbgy7lRcQMp99jhOIRBQ3astp2SwFeHjZioypLx3p3Ee5TJFchsE/IJ3u+wSu0dFEd5UyhDwI+oW6haom4Y1Y4SdL5BkJREQUmZYvxEDql403SqRc5vJ48ObRw5ifIfmTIhu9Po519QvxVucHIT+TJw+bZs+D1WzG+6dPRR24CrcQ0GsyYXjEFZKpmJOIiCidqM2HqZIjI+U8Sr7uy5cws2JKxMlhL7wBfw63KzF4HNUI9ZXVGB0fV7WAkPnsBsMmED0eD/7whz9g4sSJyM/PN+qyRJTG1JTTslks+Mf1jyI3N/3XM0iShO7Ll7ClfZdiu3Db4LsvX4p39yiDyYOg5SU3h4SqSKV0Y1nh5y/dvmCkK+YsIlKjvrIac2+9DU9tfRFOhUnEdCkbr1ake52aMttHeb5JVtj54QnFn3ecPRN14ErP4ivmpNTHjEVE9Dk143jJzpFy7htwDuO1g+1J6wcpM3m9IY9JkoS3jx0JWKylhtHlRItFm6p2zGc3xDxif/ToUXzve99De3s7rl+/ju3bt+Puu+/GlStX8NWvfhXf//73sXr1aiP6SkRpRk05rYeXrcyIyUMtJROCt8FLkoQ/fjoU7y5SFvAPVXIwCz7ryegSEOnwBSOdMWcRkVa5ubl4ZNlKQ8+7TWVKZeOtZgvLWRGAG4utlEQ7B3NL+268mvM+Bl2fl2wTzWasml2HtXULIn6emJNSFzMWEVEoNeN4ycyRLFeaPqaVlqHb0edbeDU8MoLWg3sDspRaRpcTZT7TJqZPe1dXF5YvXw673Y5HH3004GeTJk3CyMgIXnzxxZg6SETpTS6nVSwGrtooEW2GbkFPJrlkgpYAI2+D7+y14+nWl3DIfiZe3aMsIoeqzl47vvfKv+Gto4cCJg+Bz1fSdxq040L+gqEkkwaqE4k5i4j0yob8BUTOYPK97viFc0nqGaUS0WyO+RpOjztkwMvp8eCto4fwvVf+LWKuYk5KTcxYRESRpWqO1DP2Rsmzeec2PPf2G/jl7u147u03sHnXu7omD2VGlhNlPtMmpm0/f/M3f4OKigocPXoUbrcb//Zv/xbw86amJrS2tsbUQSJKf0aet5YK/Mtk2Qqs2HpAuTRWOIVWkbXaKS6OXziHtlPHo7YzsgSE/AUjeCVgiWhDS0NjzF8wIpWmy3TMWUQUi0zLX8HGx8fx8r7dim0OcoEWARiXpLhe3+XxKJ7Pw5yUepixiIiUJTtHBt/bqieWRi1LT6nFMz5u6PXkcqJG5Z5457NMEtME4t69e/H9738fNpsNnjAlQaZOnYpLl3iuFxHBsPPWks2Icgklog3VE0vxg9e3GNgzohs6VA6WRisBoTWUxesLhlJpukwPdMxZRBSrTMlfwTp77diyb7fiOY8AMBzl55QdPGNjCXkdpcVZ8vmku0+fxB+GBnFLYRFWzpwT81EO2ZyTYsGMRUQUXbJyZLh7m2ixRM19lLnkcqKdvXZsPbAXA367EYutItYv1Zd7kj1Rni5iSqtutxtFRUURfz40xDO9iChzGLVjsKWhEfar/Sy7QIazWQow7B5R3T5SCQi9g1FGf8GI9JmTS9NlUhm+cJiziIhCsYIDxYM5NzfmlfJKi7PCZasdJ7timujL9pwUC2YsIqLUFOnexsnD7NbS0IhjH58Pn3tcseWeTF1waaSYplOrq6tx5MiRiD9va2vDrFmzYnkJIqKUIElSzOUS/OvFG1m7m0i2pLpGU3u5BIS/aOdJGXV2YjRqPnOtHe2Q4lyWLJmYs4iIAhmRx4j8lYg23DP3DsPKbIXL+PHIVsxJsWHGIiJKPcx5FEweR62bWoUt7bsU225p383cEycxTSA+9NBD+PWvf43t27f7HjOZTACAn/zkJ3j33XexYcOG2HpIRJQCevoduncMmnPz8ETz/XimZYNvNUy4iRuicPJVlrYSzRbMnVKp+rpyCQh/qTQYpeYzJ6/0z1TMWUREgWLJY0Qym8WCr61YjSfXfgn/8MDDOHyux7BrB2f8eGUr5qTYMGMREaUe5jzyZ7NY8A8PPIz6ymqccfTBGabkuD+nx40zjr4E9S67xFTC9Hvf+x62b9+O5uZm1NTUwGQy4dvf/jauXr2Kq1ev4p577sE3v/lNo/pKRJQ0sewYzM3JwfTSspADoItFkeGIohpVuSLe6XHDazKpfl+1NDSG1HXXMhgV7xIPaj9zmbyblzmLiChQJv+bT4kz7HajWLShtqwC3Y4+w/J4uMVZ8cpWzEmxYcYiIko9vGeRv2G3G/ar/Tfy2mV15xJ3X76EmRVT4tyz7BPTDsT8/Hxs374d//RP/wSbzQaLxQK73Y7JkyfjJz/5Cd566y0eOklEGSGWHYNOjxtPbX0Rz739Bn65ezuee/sN/PXWFzHlplsM7CFlItFs1tR+eMSF9Q3Lo1zTErE2fCoNRqn9zGXybl7mLCKiQJn8bz4l1oBzGN2OPnSeP2vYNcMtzopXtmJOig0zFhFR6lF7zyrIz49zTyhVyPnI5PWqaq+2HWkT0w5EAMjNzcV3vvMdfOc73zGiP0REKammtCymHYPBBz4Pu9048ckFI7pGGay27FYc1XAuTqFVRG1ZBTY2NWPrgb0Y8BuMEs1m3D17Hr5QtzDigEgqDUap+cyFW+mfaZiziIg+F2seI5K1HmwPyed6lYg2tDQ0hl2cFa9sxZwUO2YsIqLUovbedv+CJXjx/bYE9oySRc5HNeW3Ascin10sqym/Nd5dykpcUkVEpIIgCFF3dhEZTcvkYfAgkReBK69yc3JQXnKz4mpqObBreZ14UfOZC7fSn4iIMhfzGBkllsnDYquIJ5rvx2Mr78GTa78UcM55sHhlK+YkIiLKNGrvbTfZJiSoR5RM/vmodnI5rFEqdIlmC2onlyeia1knpjT5v//3/8acOXMi/nzevHn44Q9/GMtLEBGljPrKamxsag4ZBDCZTEnqEdHnHli8DIIgoLPXjk1t2zDocgX8fNDlwqa2behUmJRMtcGoSJ+5EtEWsQxrJmHOIiIKpXRviDawQGSERdU1mFkxBYuqZ6C2rEIxF8UzW2V7TooFMxYRUWpSc29TsziH0p9/PhIEARsaVym2f6RxJRdOxYnJ69VfHHbevHloamrCc889F/bn3/3ud9HW1oauri69L5HWhoaGUFRUhMHBQRQWFia7O0RkEEmS0NPvwJDLiUKriGH3CDbvfDfZ3aIsVyyKeHBJI1472B615MczLRsUg1Vnrx1bO/YGXEepPFe8BX/makrLEh4Mk3FPZ86KjBkrNT4XRInm/763FVhh8nrxqXvE9xk49vF5bGrbluxuUoZTk6WCxTNbZcL9INH3dWYsZcxZRJRs4+Pj2H36JP4wNIhbCouwcuYc5OZ+fhKbvHCaMlPT7Hl4MMwCrM5eO1498H7Agvliq4j1S5dz4ZSCWO/rMZ2BeP78ecycOTPiz2tra/H888/H8hJERClHEATUllUEPtZkChkUIEqkAadT1UT2NecwevodIe9hf/WV1aibWpUyg1HhPnPZgDmLIgk3EF0siljfwC9OlLmU3vfyPUJetc5MRvGkJksFi2e2ytacFAtmLCKi1BUu8+042RXwXYeZL7PNu21a2MdTbawqW8Q0gQgAAwMDEX927do1XL9+PdaXICJKefJN7J1jH+DNo4eT3R0iRUOu6AGbg1GpgTmLgkVabTvgdGJT2zaWraOMpOV97z+wMOAchv3KZbz/0clEd5kynJosFYzZKrUwYxERpR69mW/I5cSpixfQcfZMortMBot2NjTzVOLFND07e/ZsvPnmm2F/5vV68R//8R+Kq7qIiDLN3u4Pk90FoqgKrTwvIB0wZ1EwSZKwtWOvYpvWjnZIkpSgHhHFn573vSAIcHnc+N0HBzh5SHHBLJXemLGIiFKP3sxXW1aB3JwcTh5miIXTpnNHYYqJ6W/jsccew/79+/G1r30N/f39vsf7+/vxta99DR0dHXjsscdi7iQRUTq4sdKdpRMotUVbzUWpgzmLgqm5z8il9YgyhZ73vbx6nbmM4oFZKv0xYxERpR6933XUTDxS8ljy8nDrTTepbv/BubNcEJtiYiph+vjjj2PPnj148cUX8dJLL2HSpEkAgCtXrsDr9WL9+vX4b//tvxnSUSKiVKe2lJElLw/usbE494YovJaGRq7mShPMWRRM7X1GT2k9olSl9X3PQSSKN2ap9MeMRUSUevR+1+Fi/tTUNHse5t02DTWlZejpd+C5t99Q9Tw9Z01TfMWcerds2YJXX30V69atw0033YSSkhLcf//9aG1txW9+8xsj+higr68PjzzyCG6++WZYrVbccccdOHLkiO/nXq8Xf/u3f4vy8nIUFBRg5cqVOHXqVMA1PB4PvvWtb+GWW26BKIq4//77cfHixYA2165dw4YNG1BUVISioiJs2LBBsUY+EWUWSZLQ7ejDYfsZdDv6VK1+UVvKaPWculi7RxRRiWjD46vWoFgUQx7n2WjphzmL/Km9z7C0HqWz4Aw2wVKg6nny+56DSBRPVrM52V0ggyQ6YwHMWURESrRmPhkXT6aehVXVeLBhOWrLKiAIAmpKy0LGqJScvnRR03gsxVdMOxBlLS0taGlpMeJSiq5du4Zly5Zh1apVeOeddzBp0iTY7XYUFxf72vzkJz/BT3/6U/zqV7/CjBkz8MMf/hD33HMPuru7MWHCBADAE088gTfffBOvvvoqbr75Znz3u9/FunXrcOTIEeTk5AAAHnroIVy8eBHbtt04uPUb3/gGNmzYELFOPhFljs5eO7Z27A0YfCoWRaxvWK44+SLfEJUGrWyWArx3vMvI7lKGiXWHqmdsFIJgwrMtj/oOEy+0iqgpLeNq+TTFnEUyNfcZltajdBYugxVZrRDNZjg9nojP83/fcxCJ4snl8WBT2zYuysoQicpYAHMWEZGSzl47Xj3wftR24b7rcPFk6vngvB0Leu2+rCQIAhZNq8H2E12qnv9O1we+/69mPJbiy+T1er3J7oRaf/3Xf419+/Zh797wJWm8Xi/Ky8vxxBNP4KmnngJwY3VWaWkpfvzjH2Pjxo0YHBzExIkT8etf/xrr168HAFy6dAlTpkzB22+/jTVr1uCjjz7CrFmz0NHRgSVLlgAAOjo6sHTpUpw+fRq1tbWq+js0NISioiIMDg6isLDQgP8CRBRv8pk5kUQbLIj2fCIlJaINC6qmY8fJrpivxYEtY2XDPT2dclY2/H1EEut9iihVxZKh/N/33Y4+1SWSiPQqEW14pmUDF2cZJBvu68xZREThacmA4b7rSJKEp1tfYgWKFOOflYz4O+L3XP1iva9r2oH40ksvAQA2bNgAk8nk+3M0jz76qOaOhfMf//EfWLNmDR588EHs2bMHFRUV+OY3v4nHH38cAHD+/HlcvnwZ9957r+85ZrMZK1aswP79+7Fx40YcOXIEY2NjAW3Ky8sxZ84c7N+/H2vWrMGBAwdQVFTkC1sA0NDQgKKiIuzfv1/1BCIRpRc1Z+a0drSjbmpVxMGC+spqbGxqDlk9T6TGspqZaO/5yJBrRXuvUuphzmLOUiPSfaZEtKGloZFfqigtqclgotmCvJwcDLiU3/dqduoSxYrn86SXZGcsgDmLiCgctWdXK33XEQQB6xuWczF/ivHPSkYcMcAxruTRNIH4F3/xFzCZTPjKV76C/Px835+VNjGaTCbDQte5c+fwr//6r/jOd76Dp59+GocOHcK3v/1tmM1mPProo7h8+TIAoLS0NOB5paWluHDhAgDg8uXLyM/PR0lJSUgb+fmXL1/2HaLtb9KkSb424Xg8Hnj8SusMDQ3p+0WJKCnU3NDUDBbUV1ajbmrVZ9cbRuvBdjjdbqO7SxloXJIMG/DkwFb6Yc6KnLOYsQL532dYppgygZoM5vS48T++8J8gmEyK73sOIlGisFxu+kh2xgKYs4iIwlE7sfToXU24vfzWsD+TJAlWswVzp9yGE59cMLqLFAM5KxmRmTjGlTyaJhB37doFAMjPzw/4c6JIkoSFCxfi2WefBQDU19fj1KlT+Nd//deAYGcymQKe5/V6Qx4LFtwmXPto1/nRj36Ev/u7v1P1uxBR6lF7Q1PTThAE1JZVoNvRx8lDUs3e7zD0ehzYSi/MWZGvw4wVSr7PEGUCtfer4REXFlXPCPszSZICJtUfX7UGrx1q505EihueuZQ+kp2xAOYsIqJwtIzDdTv6QhaRhTs/m1KHnJWMykwc40oOTROIK1asUPxzvJWVlWHWrFkBj91+++347W9/CwCYPHkygBsrrsrKPj9Q9cqVK75VXJMnT8bo6CiuXbsWsGrrypUruPPOO31t+vv7Q17/6tWrIavB/H3/+9/Hd77zHd+fh4aGMGXKFK2/JhElidobmpYbH29umUkwCZC8kuHXPX819N4TCw5spRfmrMg5ixmLKLPFmsHCDR4ViyIeXNKIvj/+AW8fO2JIP4lkJaINNaVl0RtSSkh2xgKYs4iIwlGbAYMrexWLIhZNq8H2E11x6hnFSjSbfVnJqCMGOMaVHLrrHDmdTlRXV+Of//mfDeyOsmXLlqG7uzvgsTNnzuC2224DAFRVVWHy5MnYvn277+ejo6PYs2ePL0wtWLAAeXl5AW0cDgdOnjzpa7N06VIMDg7i0KFDvjYHDx7E4OCgr004ZrMZhYWFAf8jotQjSRK6HX04bD+DbkcfJOnGRJB8Q1OidbCAN7fMVJCfj8dW3gvRYgl4XDRbIJrNuq87Lhk3KcmBrfTGnBWIGYsoc4TLYbFksM5eOza1bQsZkBhwOrF557vIyWFp33RWItqwes4dUXdgJVpLQyPLRqepZGQsgDmLiLJTpPE3mZoMCCCksteA08nJwxS36va5vqwkHzGgxBplLM1kMmHYPWJY/0g9TTsQ/YmiiD/+8Y+w2WxG9kfRk08+iTvvvBPPPvssWlpacOjQIfziF7/AL37xCwA33khPPPEEnn32WdTU1KCmpgbPPvssrFYrHnroIQBAUVERHntQImgbAAC2RUlEQVTsMXz3u9/FzTffjJtuugnf+973MHfuXKxevRrAjVVgzc3NePzxx7Fp0yYAwDe+8Q2sW7eOB04TpblIK9TXNyxHfWV11DNztA4WGLXKhlKL0+NGodWKf/rq10LOIAOAnR8ex+sH98W1D5a8PLjHxiL+nANb6Y05i4gykVIO05PBJEnC1o69iq+59/SHEM1mOP3O96L0cN/8RfhC3UL09Duw42RXQl+7RLThgcXLQsrglog2tDQ0or6yOqH9IeMkI2MBzFlElH2ijb8BPLs6FTXXzUdFyc24MjSAN48e1n2d6qDjNuorq7GxqTnkPSFnKwCK7wOv14vNO9+F0GRiDksw3ROIANDQ0IAjR47g61//ulH9UbRo0SL87ne/w/e//338/d//PaqqqvDP//zPePjhh31t/uqv/gojIyP45je/iWvXrmHJkiV47733MGHCBF+b5557Drm5uWhpacHIyAiamprwq1/9Cjk5Ob42L7/8Mr797W/j3nvvBQDcf//9+PnPf56Q35OI4kNeoR5swOnEprZt2NjUHPWGpvUmJQgCyypkqCGXM+wZZJIkxWWQstgqYvnMWZhUWOybrDz28XnD3quUepiziCiTRMth6+YvRtPseThoP4Nhv1XmSve1nn5H1EVaAywnn3aC/871HAmQl5ODsevXI/7cnJsHz7jyQqz6ymrUV04LWSzGBVrpL9EZC2DOIqLsonb8DYg8sVSQn4+R0dGE9ZluuL1iqm+cq7zk5pC/F7UL84ZHXCGP1VdWo25qVcRs9fiqNXh+93vwer0Rr9va0Y66qVXMYwlk8ir9jUTR1dWF1atX46c//WnAoc90w9DQEIqKijA4OMgSEERJJkkSnm59SXGQqUS04ZmWDRAEAZIkGTJYMD4+jr/e+mLAQBhlhifXfilk8jBeB3g/sGQZ7p41L+x70Kj3KilLxj2dOSsyZiyi9KImh/kTLRY0VM/AvNumKd7XDtvP4Je7t4f9GaWf+ZXTsGLWvJC/825HH557+w3DX++L9Yuw+6MTAWXRuBArORJ9X2fGUsacRUSx0Dr+5v+8nn4Hjl84hw77mZCypZQYj9+9Bguqpvv+HDzmdP36dfzfd9+Mep0nmu/HzApt5+mqzXzhxuMosljv6zHtQPzOd76DoqIifO1rX8P3vvc9TJs2DVarNaCNyWRCW1tbLC9DRBQzNSvUrzmH0dPvQG1ZRcjOMrluu5ZJms5eO7bs283Qk4FsloKQc5girbAzQlGBNeL7LdwuSMoMzFlElCnU5DB/TrcbbaeOY9qkMsVFMjxrOrOcu9KPr68qC1nMZyuwotgqGr6bVPJ68eP1fw771X4uxMoyzFhERPGjdfxNJggCXJ4bGZCS55V9u2E1W1A7uRyCIISMOX106aKq63h1nF+ttuqEnuoUpF9ME4jnzp2DyWTC1KlTAQD9/f2GdIqIyGix3ITU1G0P9xzWcM9cVRMnhayUi3YGUyw4QJqdmLOIKFPo/ZIfXMIoOH/xrOnMMuByoqffAZfHHZK9rWaz4a/3TtcHONDzEdY3LMei6hmGX59SFzMWEVH86B1/i/e4Cqnj9Hjws3f+PeK4Z7jSpOGc/Pg8bi+/VdNrqx374hhZYumeQLx69Sq2bt2KW265BdXVLO9BRKlN701IS912GUNP5jvxyQX8y7b/wO23TsXKmXNgv9oft8HLEtEWstuRMh9zFhFlEr1f8oNP2wjOX4IgYH3Dci7ayiDvHjuCD/s+CXnc9dlZO2rP3VFLKdNTZmLGIiKKL73jb1orVlB8RcpIav9+204dx/TJ5ZryVU1pWdSsJ5otHCNLMM21OSRJwn/9r/8VZWVluPPOOzFjxgwsXbqUK7aIKKXJK9SVBE/UqJkIbO1ohyRJAY8x9GSHU32f4PWD+/Ctl36B7Sc64/Y6LQ2NCSmlJZfpPWw/g25HX8j7mhKDOYuIMpGaHKaFf/6qr6zGxqZmQ69PyRNu8tBfXk4unmi+H39+VxMseXmGvW64TB8L5qrUw4xFRJQYesbfAJalTFUv79uD8fFx35+15Ho9+cobvYkiZjDjad6B+POf/xy/+MUvUF5ejqVLl6KnpwcHDx7E17/+dbz5ZvQDNImIkkHNCvXgiRq9ddsZerKL1+vFyU8uGH5dm6UADy9bkZDV8HrK9FJ8MGcRUSYyeqdgcP6qr6zG3Ftvw5b9e9DRc9qQ16DUNOBywiQIuMk2Ae6xMcOuGy7T68VclZqYsYiIEkPP+BvAspSpatg9gqe2vohHlq3UXAFEa766UcpeudKE0+OOeE1msPjQvKXhpZdewu23346PPvoIr732Grq6uvDYY4/hnXfewbVr1+LRRyIiQ0RaoV4i2sKWLdJbt52hh4zw4JJlCZs83NS2LWSyXC5X0dlrj3sf6HPMWUSUqYzeKeifvzp77fifr/2ak4dZYsjlxPEL5+Jy3VgxV6UuZiwiosTROv4GGF+xgozjdLsDckx9ZTWaZs9T9Vwt+UrvOCzADBZPmncgdnd342/+5m8wYcIE32Pf+ta38Mtf/hJnzpzBkiVLDO0gEZGR6iurUTe1Cj39Dgy5nCi0iqgpLQtbIlJv3XY1NbuJoikWbQBulF9Q837VQ22Z3rqpVQkpo0rMWUSU2fxz2IBzGK/s3wOPzl1kcv6KdF41Za4JlgJ02M8Yft1YFwEyV6U2ZiwiosTSMv4GGF+xgoznn2Pm3TYNbaeOR32OUr4KHu+aYClQ1Y/gazKDxZfmCUSn04ny8vKAx+Q/u1wuY3pFRBRHgiCo2j4vr35SKmMarm67IAhYNbsObx09FHNfKTvJh0LHu/yC3jK9FD/MWUSU6eQc1u3o0z15KOcvSZKw9YDyYAFlFtFsgddkgtPtNvy6wZleK+aq1MaMRUSUeNHG34InkOqmVmFjU3PIOAilBv8co2bMFLhRAjWccONdRVZr1A0Z4cZhmcHiS/MEIgCYTKawf/Z6Yz3mkogodeit2w4Aa+sWYPvxo/D4HTRMpJbT48bvPjiA7Se6Qn4ml1+IVPZDi1jKQ1D8MGcRUTaI5d4i56/fdx7CAO9RWSceucTpcePYx+djylbMVamPGYuIKHUoLZh+tuVR9PQ7cPzCOVW73Chx5BwjCAIeXNyIzbveVWz/+sF9qL9tWsDYaaQKIoMqFvSEG4dlBosvXROIb731Fi5evOj7s8vlgslkwquvvooPPvggoK3JZMJf/uVfxtZLIqIkkeu2B4eaEtGGloZGxUGGnJwcgBOIpNOOMJOH/owov6C3TC/FF3MWEWUDPfcW//zV2WvHm0cPx6FnlMqcHjc+jbCSPRLRbMFDd67Ay/t3w6Wwoj3WbMVclfqYsYiIUkOkCaTgBdO1ZRWYPrmcOxJTiH+OsRVELzkavPNPTbnRWPpkRDsKpGsC8dVXX8Wrr74a8vjzzz8f8hhDFxElyvj4OHZ9dBL2y5eQm5uLgtw8CDkCJhYWYeXMOcjN1fVPnua67cCN7fNKAxRE0URbB21E+QW9ZXopvpiziCid3MhfJ3D28iXk5+bCkpcPQYiev9Tcg4qtIv7iriZ86h4JyF/xGHig9DHBUoBiq6h69+n49XGIZnPUbB5rtmKuSn3MWERExpHLj/5p+FOc77+MgREXzHm5mHLTLSiyiij+7J4XPHam9by64DO0P3WP4LD9DC784Wo8fz0Kw5KXjwHnMLodfagpLdO1809NuVEl4RZ8MYPFl+bR9F27dsWjH0REMfntoX3YcaIr4qTLbw/tx+o5dfjy4mW6rq/23EQZt8VnpvzcXIym0K7SWN9nsZTppfhgziKidPLbQ/vCltv+/OeR85eae9D6pcsxs2JKyOOxDjxQeisWbWicOVv1eeOe8XGcvnQxekPElq2Yq1IbMxYRkXHClR+VHbb3+P6/XJLUv3qXnvPqBEFATWkZevodAIBL1/5kxK9BGrnHRvHCnh0AbvzdLq+dpep5/jv/Yh3HCrfgixksvjRPIK5YsSIe/SAi0i3a4BVw41wLuY3eSUQtJliib+On9JObk4PltbNSpga/EeUXYinTS8ZjziKidGFE/tJ7D+JCrewlr3y/Lkmanvcn57CqdrFmK+aq1MWMRURkjEjlR8MJLkkK6Duv7si5s/jNgT0Ydru1d5jiYsDpxJtHD0M0m+FUqPIQvPPPiHGscO8hZrD40VfPj4goRYyPj2PHyWOq2+84eQz/af4S3eVM1ejstePVA+/H7fqUPC6PB22njuOeuXdg/5mPFENSvBlZfkFPmV4iIspe4+PjUScP/SnlLz33IJ5fkr38V75rcbNoS1hpK+YqIiLKVHrLyPuXndR6Xp2aRWuUPOPXlRd1Be/8U1NuNJpI7yFmsPjgfz0iSmu7T5+E1xvttLjPeb1e7D59Mm79kVdiDbpccXsNSr4Pzp3Fj7/yF1hQFb8VTObcPMWfG11+QS7Tu6h6BmrLKhiwiIgoIq1ZKlr+0noPkgceKHNY8pRzT6xmVEzB+oblim2MzFbMVURElIn0lpGXy04C6nKcvKjnyPmznDxMcZ7xMVRNLIXNYgl4vES0Bew8lcnlRvWKtuCLGcx4/C9IRGntD0ODCXmOGnpXYlH6ueYchv1qPx6/uxmP370GYlBQMsJfrGjCxqbmkGAdKYQRERElSqLzlyRJ6Hb04bD9DLodfQAQ08ADpR732Fjcso1otqB2crmvtBWzFRERkT6xlJGXn6tmAqmloREA8Mr+PbpfjxLn/NV+DLvdEC0WNM2ehyfXfgnPtGyImK2UMtk9c+9QfC2eZZh4LGFKRGntlsIizc+RcGMgyugbjt6VWJSeBj47S2dB1XTMrZiK1z84gKuDAzCZTPiw7xPd1y22ili/9PNDxll+gYiIUo2e/BXpOZIkKd7nOnvtIWeZFIsi1jcsx9KamTjQc1r7L0ApKS8nJy7XfaRxpe89xdJWRERE+sVSRt7/uWrOq+t29MHJMw/TitPtRtup45g+uTxqtlLKZNMmTeZZhimEE4hElNZWzpyD3x7ar6mM6fsfncTxj89jfcNyQ288sazEovTTerAd+bm5OHflMnacPBbyHszNycH49euqr2fNz8c37m7GjKASC3L5BSIiolSxcuYcvH5wn+r2JpMJK2fOCXlcaXKwvrLaVxo+2IDTiU1t2zD71in6fgFKSYfsZ3Q/VzAJkLyhZ/DcM/eOsKWzmK2IiIi003t+Xbiyk9EW9XCMLX35n3mpJFIm44Kv1ML/6kSU1nJzc7F6Tp3m58kDT529dk3PCy6hJUmfD1TEshKL0o/T7camtm3YfqIr7AS2lslDANiw/G7MrJjCQERERCkvNzc3ankhf6vn1CE3N3Dtqjw5GDwAJWe0I+fPRi0Nb++/rLoPlNnCTR4CwPYTXZrzPhEREYWn9/y6SGUnlc6r4xhb+vI/81IvnmWYOrgDkYjS3pcXLwMA7DjRBfX7EG9QuyoGiL5KXu9KLMpuotmMRxpXsQwDERGlFTl/bT/RFbGNyWTC6jl1vrYyNedG/2b/HgxHKVvlHhuDCdCc/yi7aMn7REREpCxS+dFwYik7WVNahrycHIxpXJxNqYE7SDMHJxCJKO34n5VjK7DC5PVi6s0T8f9rvh99f7yKc/2XkZubC8/YGE580qt4LXlVTLQyRtFKaG1sakZ9ZTXWNywP244oksdW3oucnBwctp9hWQYiIkpZwWcVVk8sxZwplSgvuRnnrlzGkMuJ/NxcWPLyIQgCJhYWYeXMOSE7DwF150ZHmzyUzZlyG058ckHX70TZ4ZpzGGccfZhZwZK3RERERpBLTJ5x9OGjSxfRe7UfQyMjKMjLQ/lNN2P6pDKUTJgQ0/hG54VznDxMIGu+Ga5Rj2HXm2ApMOxalFycQCSitBJuF6A//x2Bh+1nok4gAtFXxahZJS+vbK6vrMbjq9bgNweir5onEs0WvLi3DYMul+8x//ewWsGDupyEJCIiI4XLXyaTKaCEt5b7l5ErklfPrUdpUQnaTgZWojCZTJhfWY2rQ4P4+I9XDXs9Sk+/2PUuNqio+MBMRUREpM6xj8+HHZ87d7UfJy9ewPqG5brvoZIk4ZX9e4zoJqk0Lhk7Wes1mQy9HiUPJxCJKG1E2gXoz39HoNp66XK7SAMGalbJyzsZXR43XjvUHjB5KJrN8Hq9cI2OquoPZQ+nJ3SSOXhXazTRSusSERHFIlL+Cj7/V8v9y6gzbWyWAgy7R/DB+Z6AycO8nBzkCgKOnD9ryOtQ+nN5PFHfn8xURERE6kQbn/PPhXVTqzQvzunpd8DJRfkJNTo+buj1hkdc0RtRWuAEIhGlBTW7AP21drTjHx54OOqZhCWiDTWlZYoDBuMqSyYcv3AObaeOhzzu9BhXAoCyh7yrFUDEsK22tG40XG1PREThaM1fgLrz5ow6N7pq4iRs3vluyONj16+z5BWF9fK+PZh7620hpXVjyVTMUURElE205MMt7bvxas77mqsu8fy89DfBUoBuRx/zUQbgBCIRpQU1uwD9XXMOw361P+qZhC0NjTj28XnFAYP75i9S9Zod9jOq+0cUzTXnMN459gH2dn8YdmK7bmqV6tK6SiGNq+2JiCgSrfkLUHe+tCAIhpwbfe5qf0zPp+wz7B7BU1tfxCPLVvpyjpbjCoIzFXMUERFlGy35UKnq0uOr1sBWUBB2gsmoahWUHKLZghfe3xHzcT2UGjjtS0RpQc/qoyGXE/WV1djY1IxiMTB8lIg2XymFLe27FK+z9/SHKI4SXmyWApZXyFK5Qg5MQbXdjar0/ubRwyHBXA7b7xz7QHVp3Ujk1faRXqOz166/80RElPb0rv5W8zxfRtM5QMTsRXo53e6AnKPluAJ/zFFERJSNjNod+Pzu9/Dc22/gl7u347m338DTrS/57p01pWWwWSyGvA4lntPjDpg8BJiP0hknEIkoLehZfSQ/p76yGs+2PIon134Jj628B0+u/RL+4YGHYTVb8Pyud6OWGB1wOdE4c7ZimyXVNZr7R5nBnJeHnz3ydTywZBlW3j4HDyxZhp9teDxk0tpoO8OUyw0nUrhXu9pekiTNfSMiosygd/V3uOdJkoRuRx8O28+g29EHSZJQX1mNP1+xWtdrMHtlH2t+vuLPRbO2gUY556gdCPVvxxxFRETZyqjdgZHO0z5y7ix6+h1YNG2GIa9DiVMi2mA1mxXbMB+lH5YwJaK0oPWsHPlsQ5kgCL5SWp29dvzg9S2aSnKVFhZhY1NzSImiEtGGloZGWM2WsOcfUuZzetw4/8erWD3njoDHo5Vms5rNcMVwPqbaszUj1Z3XstpeqQwdERFlLj1nFQZnMEC5zKPas6b9r8/slZ3unnMH3jp6KOLPH7pzBV471K76/SrnHLUDof7ttOYonpNIRESZwqizrCN5fvd7IZOLlNrmV07DilnzIHm9+Nk7/67YluNM6YcTiESUFrSelfPA4mUhX9IB4O1jRxQHHiIptIqoLatA3dSqsF/+JUmKa4Ci1BZu5bpcmi3cpPOy2lkY8bhjHvgUzWbFiUSluvNqB2x5eDkRUfbSc1ahnMEGnMP41D2CP376KXZ9GHq/03rWNAA8sGQZ7p41j9krC5WINqytW4CKkptCspXNUoAl1TWwFRTgwcWN2LzrXdXXHXI5saBqetT3UvDEuJZdizwnkYiIMolRZ1lHwsnD9HO09xxKRBvy85SrRcg4zpReOIFIRGkj0oSMvxLRhoXTpoesPraazYDXC9foqObXFc1m34CBvJNRXkV85PxZ30Si1gELyhwTLAVhH6+vrA6YdL4yNID3T58KmMQ2mUy6A/Kq2XWKE+JKB5arHbDl4eVERNktUv4Kvn9FymDR7D39Iaz5ZrhGo++sLyqwAoBvZ31j7WxdC8Mo/bQ0NEIQhIBsdfzCOXTYz2DYPYK2U8fRduo4ikUR98y9Awd6TmNYxRmZhVZR1UCo/Pr+z1PjytAA3jx6OORxOY9tbGrmJCIREaWdaONzJgCcBswuWhbIc5wpvXACkYjSSvCEjK3ACpPXi0/dIyi0ihh2j2DzztBJvFhKRa6aXRcwYBBpFfHy2lm6X4PS2wvv78BXlt4VdgBInnTu7LWHHUDSO3motBK/RLTBMz6m+L7fe/pDFFtFDCis/ApXho6IiLJPcP4qtIqonlgK+9V+358jZbBoBlxOLK2ZiQM9p6O2vTI0gKdbXwpZJGaC+tLelF5EswWPNK4MyFiCIMAVoZLDgNOJ7Se60DR7XtSBLP+co1Q5oqWhMSTjqSnfViLa8P7pU4p9aO1oR93UKpYzJSKitOOfD4MrT3DykCIxmUyonlia7G6QBpxAJKK043+eoT9JkvB060uGvpZotmBt3QLfnzt77WFXJw84nWEnhyg7DLpciqvIJUnC1o69hr5muJX48iCumrrzAy4n1s1frLhzI3i1PRERZa9w+Uv+c6wZbGb5rTj28XnFhS+i2RI2a8nPyRUEjEuS7j5QagpXTUFNrtr54Ymo135g8bKAnBMuU0U6q1DNrsVltbOi7pDlOUBERJTO/POhJEl4equxY3KUebxeL+xX+5l90ghHBYkoY9xY9WRsHe1HGlf6Bg3iMQlEmaW1ox1SmMFLI9+bJaItZKJSDu2LqmegtqwCwyMuhSt8rrSwCBubmlEsBpaPCPcaREREkZxx9MV0nysWbdjQuEqxjTfKWnZOHmYu/3wlSRJ2fng86vtNTYUHW0FoCfrgTKW0kEretRgpR5UWFkXtA8BzgIiIKDP09DsUKxwRyZh90gt3IBJRypHPF4y28jfY8QvnDOtDuHJF8ZigpMwSaRV5rO/NtXULUFZyk+rPg9p68oVWEbVlFapX28eDJEnovnwJPZcuwmsyoXZyOWZEGbAjIiLj6c1fnb12/Lp9l+7XlctICoIQsYSkmp1clLnkfOXyuBXPQtfKiMErpV2L3Y4+Vdcw8hwg5ioiIoqF3jwIcFIok8yqmIIP+z6J2/WNyD5a36uxvLezHScQiSilRDpfcH3DcsXdUJ29dk0H9ioRLRY8sGRZyOsxDJEawe8TI96btRVTNJV3UHsuj3zuT6SywPEmDzr7l6x7B4BoNuORxlXcAUlElCCx5C+lEo5q+JfLjjQZc+T82Zheg9Lf8QvnDMv6MqMm7iLlKK15LFbMVUREFItoeTDaBEyXgYv6Kbl6/3Albtc2Ivto/e6i97sO3cBpViJKGfIgVPCX7AGnE5vatqGz1x72eUaXFnW63di8810cOXcW3Y4+HLafQbejDxMsoWWOwsnNyTGsL5R+/AejjHhv6glX8rk8SpJ9vqH8eQ933pXT41H8zBMRkXGSlb8ilcsWBAE1pWUotIoYcjnR0+9QncEoc3WcPWPo9YycuIskkXmMuYqIiGIRLQ/+9tA+PN36Ep57+w38cvd2PPf2G3i69SXfveWwvQdHzsd+n5k2aTJEsznm61BslM4lj1Ws2Ufrdxe933Xoc9yBSEQpQc0gVGtHO+qmVoXcaOJVWvT53e8FnJ9SZLVCNJvhjHIjHb9+3fC+UHoIHowy4r25cNp0XeFKPpcnXCm44PK8iSZJEl498H7UdpE+80REZIxk5S9LXh7+4YGHkZsb+nU03AphtRmMMpfT4zb0eolaSJWIPMZcRUREsVCTB7ef6Ap5TJ6AWT2nDjtOHjOkL+euXPb9f6vZjNrJ5ei8cN6Qa5M68crcotmCRxpXxpR9tH53ieW7Dn2OE4hElBLUDEJFOl8uXqVF/ScPAWDQ5YrL61DmWFY7C4fP9eBT9wgmWApweXAg5mt+cO4s/mzhUt2TiMk83zCSnn6Hqs9TpM88EREZI1n5yz02hndPHMUX6xcHPB6pJCozGBklGQup4p3HmKuIiCgWsS58NmryMJjL4+HkYRLcXn4rPohhN6kJgP9oqjkvD6tn34Ev1i+MOfto/e4Sy3cd+hwnEIkoJagdhPJvJ9df77v2x3h1KyzRbIEJwLDBK6EpfYlmC7zw4q2jhwy/dqxhJlnnGyrRMujMs0eJiOJHT/6SxVpWdOep4/hC3ecDCWpWCItmCwAvdyKSbo/e1YTby29N+OvGM48xVxERUSxS/d5gMplCFvhT/Hx0qQ/FVhEDGt8XotmMu2fPw6SiErx64H043TfGTD1jY9jX8yFuvfnmmBdwaf3uEst3HfocJxCJyFDRDlWOxP/cODXtwpW3ShSnx425U27DiU8uJPy1KbU0zZ4Hq9mMN48ejuvrZFqYUft519qWiCgb6M1a4WjNX7LOXruqkolKnB5PwAIZNSuEnR43ck0sL0ShzLl58IyPRW03PJJ5u1mZq4iIKJiWvJjq9wZOHiaW0+OGOS9PdXvBZMK319yHGWUVOPbx+bDVRORyt+HOP9dC63cXvd91KBAnEInIMOEm9YpFEesblke9QdSUlqFYFBUHjuTz5SKVt0okTh5mN9FsxiONq1A3tQpPt74U99fLtDBTU1qGIqs1armt4DMliYiyXSxZKxwt+cu/D0blMHmBjCRJOH3poqrnjHslQ16bMoxJXbNMy1QAcxUREQXSmhfV5EGjmPPy4BmLvuCHkkvL31F+bi5mfLYgMN7nDWr97qLnuw6F4vJNIjKEPJgU/I+yvMqks1e5frYgCFjfsFyxTUtDI4DoNySiePv63TdWTcVyVkCJaMPjq9agWFQeyMrEMCMIAr6y9K6o7VoaGpN+XiMRUaqINWuFozZ/aSkzqsWVoQF09trxdOtLeKfrA8OuS9nDZinAuvmLVQ102SwFGZepAOYqIiL6nJ68qCYPGmVsfDwhr0PhLa2Zafg13WNj6Ol3aDpvUC+t3120tqfw+F+HiGKmZjCptaMdkqS8Yry+shobm5pDJlRKRJtvm3ushzsTxUo0W1A7uRyA9tKia+sW4LGV9+DJtV/CMy0bsGDa9KwNM/Ln3Wo2h/xMNFtiLm1BRJRJjMpa4ajJXzKjc1jbyeNhB7mI6qZWqmr34JJlKC0sUtV2SXVNRmYqgLmKiIhiy4tKefCeuXcY10eWI02aYquIh+9cgeI4VGMYcjkTdt6glu8uetpTKJYwJaKYaVllIp9zE0l9ZTXqplZFrNWeaWfBUfpxetw49vF51FdWay6DVVsxxfcZkCQJ3Y4+jF+/jnXzF6P99KmAQ6pLRBtaGhozOszIn/fuy5fQc+kivCYTaieXY0ZZRcYO8BER6WFk1gonWv6SGZ3DXKMeQ69HmaOmrALHPu6N2u5T9whcbreqa867bVqMvUptzFVERNkt1ryolAenTZocUhaV0sv6pctx4uIFjF43fheoEecxazm3U+13F73tKRAnEIkoZkavMhEEIeLgVyaeW0LpR67bruWsAP9SpOHOJCiyWnHf/EWYVFicVWFGEATcXn4rbi+/NdldISJKWYlY0auUv2TMYRQLk8kEr4qdByWiDStnzsGOk12KGctkMuH1g/tUvXYmloQPh7mKiCh7GZEXI+VBeQJm54fHVd97KXXcM28++v74B7yl48gAm8WCYYXFWv4ZS+95g3rOeVfz3SWW9vS5zB+ZJKK4UzuYpNRO3o112H4G3Y6+iCW45AkbomSSV+1pOStALkUa6UyCQZcLbx49jNycHNRypTgREfkxImtFojaDAcxhFBuv14ulNbVomj1PsV1LQyNyc3OjZiw1k5H+12S2IiKiTKY2Bw6OuHSVvRcEAXfPmheXEpgUX9uPH9U1eVgi2vDVpSsU28gZS+95g/E4552MxR2IRBQzNbuwlFb9allpIt+QNrVtM6bzRDrJq/bkeuqRynn4lyJVeyZB3dQqDnIREZFPrFkrEq2rfZnDKFYHerqxsakZ0yeXh7z3gsu3R8pYancyhrsmERFRplJbIen1g/uw42SX4u6uSARBQOPM2Xjr6KFYukppQs5QgmCKmtuAyNktUh7jGFl64AQiEcVMzWBSpFW/8kqTYPJKk0gH4N4z9w5sP9EVc9+J9PJf3edfT33AOYxP3SOYYClA8WeDufJ7P95nWBERUWaKJWtFoieDERmhtaMdz7RsUHUWTfCZNYMjLlWl075wx0LMLL81a0rCExERaVnoFUveKy0s0ttFShPhFnWpPUNQS1uOkaUHTiASkSG0rjIB9K80kSQJh8/1GNd5Io3C7fJQU089EWdYERFRZtKTtSKJJYNFex5RNP4DQWoGg/wz1mH7GVWvUV5cwoEmIiLKOtEqJAXTs7uLZ2JnLqUFWFrOEFTblmNk6YETiERkGC2rTAD9K03UPC8WNksBpk0qxfGPe+P2GpTe9J6jE88zrIiIKPNpzVqRpFoGs1ksGHa7Db8upa7jF87pmuBjliIiIlIm58WdHx6Pumtfz+4utaVSKb2UiDbcV78ooZUbmOvSA2t5EJGh5FUmi6pnoLasQvHGo3elSbxXnnx58Z34+I9X4/oalJ5EsyWmkm5y0Fai5wwrIiLKHlqyViSplsEeXNKI++Yvisu1KTW1nTqOzl675ucxSxEREUUnCAKKCqyq2mrNd3KpVMosehfKx4K5Lj1wApGIkkbvSpN4rzxxetxcSUVh5eXkoG5qle7nqwnaWkObJEnodvThsP0Muh19kCRJd/+IiCg7pFoGKxZt+GL9YmxsakaRVd1gF6W/1o52zbklHlkqEmYsIiJKZ0bu7gq+J9ZNrcLGpmaY8/Ji7SYlWYloS9rZ52py3fzKaejpdzCHJRFLmBJR0qgpe1Ai2lA9sRTdjj5fqa7qiaUotooY0LEK3pybC8/4eMSf2ywFuDo4oPm6lB0GXM6YD2828gyrzl57yHWKRRHrG5YnJfwREVF6UJvBakrLIEmSr2Sq1VIAk8kEr9drWF/8VxXXTa2CJd+Mt44chP3KZcNeg1KTnrJpgLFZKhJmLCIiSnda8p6SSPfEB5c0wpKbB8/YmGF9psS6b/4ifKFuYcJ3HvqLlOvk7xxtp46j7dRx5rAkMnmN/PZHAYaGhlBUVITBwUEUFhYmuztEhvIfTNJ7/g5wI4hsatsW8ef3zL0Dh8/1hASV6ZMm44Pz2sseiWYLnB6esUP6PbbyHiyqnhHzdWL9DEX77CRrBVmm4j09tfDvgzKZURkrGjX3EQAhX+a1MgFQ+sIp36/CDU5R5guXq9R+BuL1WWHGSjze11ML/z6I0ke0e2Gs97Roz6f0ZTWbsaFxVdi//0R9Hwn3mscvnEPbqeMR2zGHaRfrfZ07EIlIMyNX5CqtIF44bTq2n+gKec6A06lr8hC4UZ503fzFaO8+xQEq0iVceQ894Uo+w0oPSZKwtWOvYpvWjnbUTa1K6koyIiLSJpG7nqLt4gJgyICRFwibvfx3i3FwKnv55ypJkvD2sSPYdeoYnB6P7/FIn4FYslQkzFhERJQu1OTGWHbtq7kn6iGazQH3eUoOl8eDTW3bsLGpGXVTq3xjWv1Dg2g/fSqg6lukLGbkRKMgCKgpLcMLe7YrtmMOSzxOIBKRJpEGeAacTt+NR88kov/NSi5T+oPXtxjV7QClhUV4tuVR9PQ7MOAcRuvBdjjd3JWYzdSWYxPNlpDyHskocXXjvas8Aa63LBgRESVHPDJWNOEymHyfe7r1JcNexz97BQ8wxGtwilKff9m0zl47ft2+C64wA4rx/AwEY8YiIqJ0oCU3Rsp70SZg1NwT9cjLycUTzWvwqXsEEywF+MXObXCNjhr+OqTOlvbdeDXnfQy6XBHbhHtfxWMsjDksNXGqlohUU7siV8/BtvIK4kXVM1BbVgH71f647RB0XPsTevodn9WDt3HykLB6Tp2u58mhPfi9Koerzl59O2WjGVJ5/qfadkRElFzxzFjRBGcwQRAMHzAqtIohrwMA3Y4+vHX0EKtCZKmWhkYIguDLU+EmD/3F6zPgjxmLiIhSnZ7cGC7vRROve92AywmTIGBR9QzMKKsATKa4vA6p4/S4FScP/cnvq3iNhTGHpSbuQCQi1RK5EiSeN4O3jx3B28eOoFgUsYB1s7OazWLBw8tWor6yGua8fLx19JBie6fH7Xt/J7PEVbgyqrG0IyKi5Eq11bZG5rCC/HxUTywNeIznHWY30WzBI4038peWHaiJ+AwwYxERUapLVG6M571Ozpo9/Y6oC4godVxzDuOMoy9uY2HMYamJOxCJSLVErgRRezP4Yv0imHSuVhpwOhUP5qXM11g721daobSwSNVzTl+6iMP2M9j54XHVod1oN3bPKn9G/MuCERFRaku11bZGfikfGR3FD17f4luJHGnFMmUea35+yJ/vm78I//TQ11A3tUrXDtR4fwaYsYiIKNUlKjequSfqdWVoAAB3kqWj7suX4jYWxhyWmrgDkYhUS+RKEPmmoXRTKhFt+OIdC1FechM273xX92upPf+OMk/neTsEADXlt2KCpUDVc97p+kDTa8QjEAuCgPUNy8OeeSCTy4IREVHqS7XVtmpyWLFVxLIZs/D7rsNRryeXM/pi/SLs6/7QyK5SCvv6qjXIyckJOW8plh2oEywF6Hb0aTrDSQtmLCIiSnWJyo1q7ol6vXn0MLwwYVpQlQpKfSaV46d6xsKYw1ITJxCJSDW1k3pGrATRctNYUDUdQpMJW9p3wamj9AEnD7NX/9AA3j52BDh2BAX5+RDNZl3vISXxGuytr6zGxqbmkAG4EtGGloZG3YdWExFR4iUyY6mhJoetX7ocAGA1m1WXnvp9Z/TJRsoc5644sG7+koDH5B2oeohmC154f0fAOT3Fooj1DcsNzT3MWERElMoSmRsj3RNFswVOjzuma7919FBItQJKbSWiDTXltwLHjkRtq3csjDks9XACkYhUS/RKELU3DUmScPFPf4xp4mfKzRPxyR+vxtxnSl8jo6OGX9Oo0C5JEnr6HSGr7esrq1E3tSrsz4iIKH2k4mrbaDkMQFxWpFPmeKvzA1TcdEtAZld73mE44QYq5d2tG5uaNQ8oRcpXAJixiIgoZSVjbM7/nnhlaADvnz5lyLVdcRiHofh5YPEy1E4uj/sENnNYajF5ufUmboaGhlBUVITBwUEUFhYmuztEhjly7ix+c2APht2ff4mP50oQpS/3nb12vPT+ToyMMXSQMaz5ZuTn5mLAgNKjegazgoUr8xWP1fakjPf01MK/D8pU4f7NLxFteGDxMtgKCpLyBTpcDgOAJ7c8D8/YWEL6QOlLNFvwTw99DYIgoNvRh+fefkPXNbzwKu50LRFteKZlg+rPBfNVauF9PbXw74MoPYS7l4lmM1bNrsPaugVxyYqxVBKg9CdnJUB5IaERY2FknFjv65xAjCOGLspEYQOKxYKH7lyBBVXTE94XBheKhy/Mmw+xoAATLAXoH7h2o8ypBv4T6koT4NFEe48zlCUO7+mphX8flMmC7xvD7hG8drA9pSY6ftG2DUd77Ul5bUo/315zH2bdOhWH7Wfwy93bVT/PnJeH2RVTUDVpMn57aH/U9k+u/RJqyyqitmO+Sj28r6cW/n0QpQ9JkvDOsQ/Qdup4wEKbeGRFSZLwdOtLus4wptSVl5ODsevXNT1nY1MzALDMaJqI9b7OEqZEpFqkL9tOtxubd74LocmUsJuEJEl4Yc+OhLwWZZ93jh8FABRbRcysmKL6eStvn4P6qum+ScJYVrerKfPV2tGOuqlVLONARJRBBEHwTYJ09tqxeee7IW1iKdsYq8Pnejh5SJps2rkNf3FXk+qzcOZXTkP35Utwut042nsOR3vPqXrekIrqEcxXRESUSY59fB5vHg09YzoeWbGn38HJwwykdfIQuJGVnmnZwDKjWYJ/o0Skitov25Ikxe31ux19OGw/g25HH946ehij4+NxeS0i2YDLiY6e06rb11dNR21ZhW/ycFPbtpCALQf5ziiDr2rC+TXnMHr6Har7R0RE6SOZ2Ss4d8mv0dlrxy93vWf461Fm84yNYVPbNpxx9EE0mxXbimYLjvaeg9Mdet5hNGomKJmviIgoUyQ6Kx6/oG5BD2U+OSvJCx8XVc/wjYVR5uEORCJSRcuXbTWlg7QIt4uLKNXIh0RLkoTuy5ewpX2XYvtoq9vVrKLX0o6IiNJLsrJXpN3zX160DFs73jfsdSj7/L4zdIdEsPHr+hYIyjksGuYrIiLKFInMipIkocN+JqZrUGYZcA4nuwuUIJxAJCJV4vVlO9r5cDznkNJFS0Mjjn18XvVkd7Qgr7bMl9p2RESUXuI50REpf0XKXQNOJ365mzsPKf48OiuMtDQ0qlr1znxFRESZIt6LYvzz4uCIS1d1AMpcrQfbkZ+by/MOswAnEIlIlXh82Y52Ptz4+Dhe3rdba1eJEko+JBqA5slupSBfU1qGYlFUnIxUu9qeiIjST7wmOiLlrweXNOK1g+2arkWUbHIOUzt4xXxFRESZIp6LYo6cO4vfHNiDYU4aZhTRbIbT4zHkWk63O2lnslNicQKRiCLyX21kK7Ci2CpiQGHCI9KX7XCr3I99fD7iCvdNbdswd8pt6Ll8Ce6xMUN/JyKj1N1Whbtn1/ne80+3vqT5GkpBXhAErG9YrjgpqXa1PRERpQ85Nw04h2GzWBQHbkpEG6onlqLb0RexmoM/pR2Gm3e+a9jvQBRvotmMx1etwQyN5+0wXxERUaZQsyjGZilA9cRSxesEj9md+LgXO052GdxbSrb75i/CtNJy/Oydfzf0utGO56H0xwlEIgor3Op0q9ms+JxwX7bDXafIasX49euK1zrxyQUdvSbSR88qrIrim3zlR7sdfZrP6FSzur2+shobm5pDPkNaV9sTEVF60Hru88Jp0/GD17dErObgT5IkbO3Ya2h/iZLF6fHAJAi6BquYr4iIKBOoWRQz7B7BD17fEjYbAtqzJ6Ufk8mEr6+8FwumTYckSVEnnbWKx5nslFo4gUhEISKtTnd9NsESPNkS7su2JEl4+9gRvHX0UMh1Bl2uOPSaSL+G6bVoO3Vc03Nqym/1/X89ZwqoXd1eX1mNuqlVimeFEhFR+tNy7nOJaMPCadOx/URXyM/kag7r5i/G2roFvvvFjV2NHByi1CaaLXB61JVL03umE8B8RUREmSHSohh/cjYMLjWpJXtS+vr6qnuxoGo6AHWTznrEksko9XECkYh8JElC9+VL2NK+S7FdXk4unmheg0/dI2G/bHf22vHqgfc5UUhpY95t0zB9crnqlXei2YLayeW+P2s5U0DP6nZBELiai4gog6k599lmseDBJY0o/qxs6Q9e36LY/q2jh7D39El8ZeldqK+s5hd7Soh18xejvfuU7snqRxpXou/an8IuQgym50wnf8xXRESUCeorqzH31tvw1NYX4VQofe9fapKVKTJfpLGnSJPOWhZxBYs1k1Fq4wQiEQHQVrZgwOWESRCwqHpGwONKuw6JUpVcSlQQBN9K9OMXzinuSHykcWXApLmaswf0ntVDRESZrbPXji37disO+ADAsNuNYtGG2rIKnO77RFVmG3S5fCvO+cWe4q1EtGFt3QKsrVvg29l3ZWgAbx49rOq58iBX3dQq7D19UnExoppS8ERERNnCfrU/apb0LzXJyhSZ7Vv3fBG33zo14thTpEoMxz4+HzI2bDKZ4PV6I74WM1nm4wQiEekqWxC8ir2z145X97+PwRHuOqT0Mr9yGnr6Hb5JxNqyCtSWVWD65PKQnbTFVhHrl4aeHaCmDMQjjasws2JK3H4PIiJKP1oz2JDLic5eO34dpVpEsNaOdvzDAw8bfuYJkb9ltbNw5PzZkAol5SU3hwxGFVtFLJ85C5MKi0PaC4KAryy9S/GzobYUPBERUTZQW2ni+IVzqC2rwIBzOM49omRyDA1gtlCp2CZcJYZwE4vD7hFs3vluxOswk2U+TiASZTm9ZQv8V7GzbjqluoaamTh+4Txco5+f3Smvomo7dRxtp46jWBQDDhbXejZOpDIQekqWEhFR5tOTwdTu5gp2zTmMs/2OuJx5QmTJy4fXKwVUIfHPVXrOG2SuIiIiUm+CpUBVu7ZTx1FgtsCcwymBTPaHoUHdzw03sSg0mZjJshj/tSDKcnrKFvhvT5ckKeqZiUTJZMnLgzUvDyZT4OPBJRjCHSyudDaOJEkhA2FKA2Th2nOVFhFR9tKawUpEG94/fUr36/1i17tYNuN23c8n8lc3tRKCkIMPL34M99hoyM+Dc5XWTCUIQthcVT2xFPar/ThsP8M8RURE9Blv8ICHgreOHoIll1MCmewm2wTFn2sdn6qbWgVLvhk9ly7CazKhdnJ5wPE8HO/KbPzXgijLqS1z4M9/e/oZRx+cHk+UZxAlj3tsDDs/PKG6vf/B4pGEOzPUf6V98ABZtPZERJR9tGawZbWzYjpn2uXxYPuJLt3PJ/J37ONeVe2i5apoGcl/4rGz144fvL6FeYqIiCjIsMbjhNzj43HqCaUi/wm+/qFBtJ8+hQGXujwVLqsd8GvP8a7Mx6lgoiznX4o0mhLRFrA7CwC6L1+KR7eIkkY+WDwSuWRv8K4ReaX9W52Hcdh+Bt2OPkiSFLV9Z689Lr8HERGlNrUZzGYpwMamZpQWFsW5R5+/3j1z70CxqD4jEkWilKu0ZCTmKSIiosi0jO1R5vvj8Ke+/9/Za8fTrS/hubffwC93b8dbRw8FTB4CkfNUtPz120P7mM+yAHcgEmW5mtIyFIuiYgkt0WzG46vWBGxPl5mCykASZYJIB4qrOa/Kf3dIkdWK8evXFdur2fFIRESZR00Gs1ks+Mf1jyI3Nxfdjr6E9OvBJcuwZHotKieWYvPOdxPympTZwuUqNZlKzkgAVLdlniIiomykJldS9pBHauUJQLX885SarLbj5DHV16P0xb89oiwnCALWNyxXbPNI4yrMrJgS9h/8mvJb49U1oqRpPdgedqWU1vOqBl2uqCV+o+14JCKizCQIAh5c3KjY5uFlK5H72Rk18sBQvBWLNkiShNcOtsf9tSg7hMtVajKVnJG0tCUiIsoGkiSh29Hnq34EIOrYHmWPqomlGB8fx8v7dmt6nn+eUpO/vFE2lTCfZQbuQCQi1FdW4565d2DHyWMB//ibAMyvmu5b+QuEORh30mRYzWa4eA4iZRCn241Nbduwbv5irK1b4Js813NmqBrxui4REaWuzl47XjsUfpJONJuxanZdQAaTF31pWUWslclkQvXEUs0LZoiUyLnK/yiESNUegg04hyGYTKraMk8REVE2UDpzbmNTM7a074q6kJky25+Gh/DU1hfhdLs1P/f0pYsYcjnRd+1PhvSF+Sz9cQKRiNDZa8f2E10hj3sBHDl/Fh9d+gQbGlcBQNiQsmzG7WGfT5Tu3jp6CHtPn8RXlt6F+srquJ0rwPMKiIiyS7RyQk6PB28dPYT27lNY37DcN+lSX1mNjU3N+NX7bfCMjRneL6/XC/vVfn7Rp7jwL2P1qXtE1XM+dY9gys0TVbVlniIiokwXKUPKZ85tbGrGQ8tW4le7t2NMkpLQQ0o2S14+3jx6WPfz3+n6wMDeMJ9lgrQuYfqjH/0IJpMJTzzxhO8xr9eLv/3bv0V5eTkKCgqwcuVKnDp1KuB5Ho8H3/rWt3DLLbdAFEXcf//9uHjxYkCba9euYcOGDSgqKkJRURE2bNiAgYGBBPxWRImlpqa1y+PBprZtEQ/G3X6iC/fMvQNFVqvq15075TZd/SVKtEGXy3f4czzKx5WINtSUlhl6TSIjMGcRxYea7CWTB4OCyz8qTR7GmrHkKhNERvMvY/WnT4dUPedPnw6pyl/MU5RumLOISCs1GXJL+25s3vmu6slDrWN5lPrcY6PJ7oIP81lmSNsJxMOHD+MXv/gF5s2bF/D4T37yE/z0pz/Fz3/+cxw+fBiTJ0/GPffcg08//dTX5oknnsDvfvc7vPrqq2hvb8fw8DDWrVuH69ev+9o89NBD6OrqwrZt27Bt2zZ0dXVhw4YNCfv9iBLFqBJVH5w7i2ce3IAn134Jj628B0+u/RIev3sNioMGoEpEGzY2NaNpdl3Mr0kUC2t+vqb2rR03yswZfa5AS0MjD5SmlMOcRRQ/erJXa0c7JElSNXB08U9/xNdX3gObxRLwePCfI5lgKUjYeYuUfYZcTkiShIPnelS1P/RZu2j5i3mK0glzFhHpoSZDOj3qSlbKY3NfXrwMP1r/53hy7ZfwtRWrcdfMOUZ0lQgA81mmSMu/weHhYTz88MPYvHkzSkpKfI97vV788z//M/7n//yf+M//+T9jzpw5ePHFF+FyufDKK68AAAYHB/HLX/4S/+f//B+sXr0a9fX12LJlC06cOIEdO3YAAD766CNs27YNzz//PJYuXYqlS5di8+bNeOutt9Dd3Z2U35koXowqUXXNOQz71X7UllVgUfUM1JZVQDCZ4EXggbqS98YqKK/Ks0yI9DLn5oVMYNssFjTNnocnmu/HF+5YqOl68qp5uXyc2oFYJevmL/aVpSNKFcxZRPGlJ3vJ9yA1A0fXnMP4TcdeDPudeSJaLFgxc7aq1/KaTL7zFomMdmVoAD39DtVn8gy73QH5K3hiWx4AZZ6idMGcRUR6GVli/tG7mnz3TkEQ4PK48bsPDuD90ycNew3KXsxnmSUtz0D87//9v+OLX/wiVq9ejR/+8Ie+x8+fP4/Lly/j3nvv9T1mNpuxYsUK7N+/Hxs3bsSRI0cwNjYW0Ka8vBxz5szB/v37sWbNGhw4cABFRUVYsmSJr01DQwOKioqwf/9+1NbWhu2Xx+OBx++Q2qEhdWVZiJLJyBJV/mEmUl12uRxk0+x5IT8jMpJnfAz/9Z61EEwmXzm2mtIydPaew/O73wsYWFVLfo/XV1ZjdHwcL+zZEVMfSwuLYno+UTykYs5ixqJMojd7aRk0Cp6ccbrd+H3XEdWv89Gli/jkD1dx28RJuHD1iqZ+Unaou60Kxy6c1/y8nadOYGhE3fmHMv/8VTe1Cj39joBsx5XtlE6Ys4hILyPH74ZHXL7/H+1sbiI11tYtQFnJTcxnGSjtJhBfffVVHDlyBB98EHqg5+XLlwEApaWlAY+XlpbiwoULvjb5+fkBK73kNvLzL1++jEmTJoVcf9KkSb424fzoRz/C3/3d32n7hYiSTC5RZUQZUznMqCmvddB+JubXI4pmeMSFRdUzfH/+7aF92H6iS/f1/AN7sWiLpWsh1yNKBamas5ixKJPozV6Jume8sn+P4hmLRACQo7OaiNPjxp6PtO1u8H/vC4KA2rIKXa9NlGzMWUQUi2SN3xGpUVsxhRktQ6XVVPAnn3yC//E//gdefvllWBRKx5mCvsx4vd6Qx4IFtwnXPtp1vv/972NwcND3v08++UTxNYlSgVElqvwPxlVTXmvY7TakBCSREv8BpyPnz8Y0eRh8+HOs50PxMGlKNamcs5ixKJPoyV7yPSMRZxNy8pDUOO3oS8jrMC9RpmDOIqJYqcmQ1nxz1OsUf7ZDDNB3NjdRMP/3FGWetJpAPHLkCK5cuYIFCxYgNzcXubm52LNnD/7v//2/yM3N9a3UCl5VdeXKFd/PJk+ejNHRUVy7dk2xTX9/f8jrX716NWQ1mD+z2YzCwsKA/xGlA/lMEdEcPWhEsqx2Fo6cP4tuRx8GnMOqnrPEb2cYkdH8B5wkScIr+/fEdL3gw58FQcCDixsNux5RsqVyzmLGokwT6Ty3SOR7Bs8mpFRgsxTA5VfuMJ6YlyhTMGcRkRGinQm8YfmqqNdYv3Q5BEGAJEk4felivLpKKUY0W9AQp3HYB5c0oqffgcP2M+h29EGSpLi8DiVHWpUwbWpqwokTJwIe+9rXvoaZM2fiqaeewrRp0zB58mRs374d9fX1AIDR0VHs2bMHP/7xjwEACxYsQF5eHrZv346WlhYAgMPhwMmTJ/GTn/wEALB06VIMDg7i0KFDWLx4MQDg4MGDGBwcxJ133pmoX5coYSRJgtVsQUvDcnx06SKOXzgP1+jngwIlog0tDTcmSrZ27A1YnSSaLfDCi7eOHvr8MZU7C+fdNg3TJ5eHXJPICP4DTj39jpDzoNSS3//Bhz939trx2qF2xecAoZ+ZSNcjSjbmLKLE8j/PbcA5/FkGOwfX6KivTaR7htVsDpnAseTlwz02imjWzV+M9u5TAfcmm8Wi62xgyk5VEyfhxCcX4voazEuUaZiziEgtSZIUz/uNdibwxqZmbGnfBWdQVhTNFjzSuBL1ldXo7LVzLC7LfOXOu2CzFKBDw5FS/mNbkd5Td86YidcOtQe8l4pFEesbljPHZYi0mkCcMGEC5syZE/CYKIq4+eabfY8/8cQTePbZZ1FTU4Oamho8++yzsFqteOihhwAARUVFeOyxx/Dd734XN998M2666SZ873vfw9y5c7F69WoAwO23347m5mY8/vjj2LRpEwDgG9/4BtatWxf2wGmidBIcRIZHRkL+oS+yWnHfnEWYVFgcEkT8Q8qVoQG8efRwyGuomaiRd4cJggDJ68Ur+/fonuAh8mezFODhZSsCgsqQS18ovm/+InyhbmHIyvdoh4w/sGSZ7/XDBXsA6Hb0RfxCQJQMzFlE8aE0CCQIAlweN373wYGALGY1m9E0e17IPUjp/uMeG4VoNod8sfdXItqwtm4B1tYtCMhzO04eM+i3pWxw/mro7iaj3D1rLuoqq6Nmo2iDq0SphjmLiNQIN7GndTJGnmA84+hD9+VLMHm9qCm/FbWTyyEIQtTxDMpM/9+h/fjSwgZVbVfePgf1VdMD8tXcW2/Dro9Own75EvLz8tAwvRYjY6PYvPPdkOcPOJ3Y1LYNG5uaOYmYAdJqAlGNv/qrv8LIyAi++c1v4tq1a1iyZAnee+89TJgwwdfmueeeQ25uLlpaWjAyMoKmpib86le/Qk5Ojq/Nyy+/jG9/+9u49957AQD3338/fv7znyf89yEyktoVRoMuF948ehgbm5pDDsAVBAG1ZRWQJAlPb31Jd1/k3WGdvfawNxsiPSx5efjH9Y8iNzfw9uZ/FqIaSqve1Rwy/vrBfai/bZqv3Jz/58iILwREycKcRaRNtH/zIw3guDwevHn0MMpLbvbdG9TcfwDlc7L8d+fXllWgs9cedjEYkRL5LHOlXasmkwler1fztTsvnMcDS5TLljJLUaZiziLKbpFyYfBkjJr7oCAImFkxBTMrpgRcS5IkbD0QLU9SJrrmHMan7hFVbeurpkcdx+p2XMT49euK12ntaEfd1Cou8kpzJq+eVE+qDA0NoaioCIODg6whT0mnZ4VRiWjDMy0bwv5D//vOQ6oGnIIHF/wnZiRJwtOtL7FkAhlm3fzFWFe/KORxte+1VbPm4Y7KaYqr2LsdfXju7Tei9uXJtV9CTWlZyI7fzbsiT5hzdVbq4j09tfDvg9JBtOz1+N1r8NrBdsV7k38WU3v/CVeiNNzCGOYwikXT7HloO3U84s8fv3sNbJYCDDiH0XqwXVOlkSfXfilkEaMs2ueKWSo98b6eWvj3QZR4anJZiWjDA0uWKS7Cj3YfVDuWR+klVxAwruLcwa+tWB1S+SRY8FjwkXNnFcexolHKdZQYsd7XM24HIhGFUrdiPdQ15zB6+h0h/9AfOXdWdeB4cEkjikUbBj5b6TLBUgCr2eIrO8RBKzKKOTcXa+sWRCxptb5hueKA0z1z78CXFy+L+jpqy6Eev3AOL+zZHvAeN5mUd4ZwdRYRUWZQk71+s39P1HMH5SxWU1qG3R+eUGwrKy0swrMtj0Yt73jG0cccRrpFOss83GR1fm6upoWMkbKWms8VsxQREaUjNeNj15zDeGX/HsU2SvdBLWN5lF7UTB4CQLFoizo25l+x5Mj5s3h+93sx9U3vkUKUOjiBSJQFYpmoC/6H/rC9B/+m4eZRLNrCnu1TLIq49aZbdPWJKJx75s3HsY/Phwxk2SwWLKmegXm3TcPjq9aEnPlps1jw1TtXYEHVdFWvo7YcarhV+dE2/UeatCciovSiJntFmzyUHb9wDv+2+z0Mulyq2l8ZGggpnx2ss9eOX7fvUnU9omCWvHwMOIdRLNrwwwcegf1qv+JkdX1lNTY2NePlfbtVve+vDA2EfVzt4CqzFBERpRu1kyzRdvRHug9qHcujzFMi2nw5bWNTc9RFYEYdOaX1SCFKPZxAJMoCsaz28P+H/reH9mH7iS7Vzy0RbRh2j0Q8UJer3skootmCsuKSsKuoht1utJ06jrZTx1EsinhwSSNslgLFgS4lNaVlKBZFxfev3nN/AK7OIiLKBEb+W65UJjKc4LMTg+kpa0/kzz02ihf27ADw+ZlLi6pnKD6nvrIac2+9DU+9+iKcHuXBz72nP8QX6haG5DO1nytmKSIiSjdGTrIE3we1juVRZvLfWVhfWY26qVURK5borWQXTJ60pPTGuh5EWUBvEPH/h/7I+bOaA8cDi5fhtYPtul6bSIuH7lyh6r024HRi88534fK4sah6BmrLKqJOHkqShG5HHw7bz6Db0QcAWN+wXPE5sRwvzNVZRETpT+2/5TaLRfHn0UpfR9La0Q4pTCkjowYDiGQDTic2tW1DZ6894PHg/CRJEnJzc7Fq9rzo13Q50dPvCHlc7eeKWYqIiNKNvFBZic1SoOpa/vdBPWN5lFlKRFvYszHliiXhxsaMOnLKf9KS0hd3IBJlATU7psKR/6GXJClqnfVg6+Yvhq2ggLsMKe5yc3JwefBPmt5rW9p3qzofp7PXHlLWQV5pH6nkw/zKaZp3i/g/n6uziIjSn5rsVSLa8MDiZdi8K3JpIL0LUsKVr5IkCTs/PM5sRnHx4vs7MTo+jmLRhuGRkZCS8XJ+Ki0sUnW9cLsI1X6umKWIiCjdCIIQ9Wy6ry69K+T+Gsz/PqhnLC+SL96xCDtOdsIzPm7I9Sgx1tYtwLr5izVP4mmp5mDOzUNBfj4GXJHLoVJ64wQiURZQE0T8Bf9D39PviFpn3V+xVcTaugU4cv6srv4SaTF+/brmg8CdHjfeOfYBvli/OGKbSCXe5JX2G5ua8WzLoyElH3r6HbonELk6i4goM6jJXnLWEgST4QtSgMAv/uEWxBAZyb+saThyfrpv/iJV1wu3i1Dt54pZioiI0pF8ZrDS2XSCYFJ9H9Q6lheOaDbjkcZVuPinP3LyMA3VVkzRlYu0VHPwjI/h0bvujumoIEptnEAkyhJKQeSBJcsU/6HXeo7Igqpq9PQ7MEFleQWiZNh56njY83UAdSXeWjvaUTe1KuRwcj1nJHJ1FhFR5lEzCCS3C3cGSSwLUgD4chjPPKRUsvf0hyi2igGr1IMp7SJU+7kiIiJKR9HOptNyHzTiTOCv390M96gHv+/Utmib4s9qNsPl8UT8eSxVGbRWsnv94D4807KBk4YZihOIRFkkWhCJROs5Im2njqPt1HEUWa0QzWY4FW5oRMni9HhCyrvJ1NR7D1ceDlC3Ov7rq+7l6iwioiygNnvJZ5D4qyktg81iwbDOleMvvL8DLQ3LeR41pZQBlxPr5i/GW0cPRWzT0tAIAOh29EUcPNXznYaIiCgdhMuF/tTeB2M9E7hEtKFm0mQ89eqvYroOGasgPx+PLr8bAAypyiBJUtj3kpZKdpHGxygzcAKRKMtECyLh6D1DcdDl0tSeKJjJZMLK2+di14f6d2AoibQiT+1KvUjt6iurcc/cO7Dj5LGAnYYmkwmr59RhQdV07Z0lIqK0pCd7yc/76tIVimckKhl0ubB5p77nEsVTaWGR4u4JAHi69aWwZyjKOyv0fq6IiIgygZr7oN6xPNnCadPx7omj3BSQYlr88lCsVRnCHXPgn7k2NjVjS/suVe8BI3a8UmriBCIRRaV15UmwSAfqLpw2HYfP9fA8HorIkpeHoZH4vT8irchTu1IvUrvOXju2n+gKedzr9WL7iS5MmzSZJbaIiCiqBdOmo/cP/WHvKUSJEMsu2EgKrSJqyyrC7p449vH5qGdQM0MRERFFF+tY3oGeboyOjRrcK4rVTbYJvv8fS1WGSMccBGcuS74ZP3vn36NeL9Ydr5S6OIFIRKpEqrNuycuHO0qg8IyP4Z65dagpu9V3Q6ueWAr71X7cetMt+NQ9guGREWw7fjTevwalmZHRURw5b4/LtZXqwatZqRfp+WrPT7TkmzE84mLZLSIiUvTlxctQObEUr+zfA6ffRI5otsDpMXZih8hfsVXEDx98BPar/RhwDuOV/XvgGRuL6Zr++Sl494SWM6gFQYhYcouIiIhu0LqLzN+weyROvSK9wo1D6anKoCZzvbxvD0bHx1FoFWM6v5rSHycQiSiscF/Iw61sGXAO44U9O6Jeb9eHJ7D2jkUQBAGdvXb84PUtAZMzPC+REk2pHryalXqRnq/2/ET/FVzBZbmIiCjzxDLZsaBqOupvm+Z7/gRLAV54P3r+IorFg0sakZub6xuUys/N1b2LQaaUv7ScQe3yuBVLbhEREWUyLbmybmoVXs15P8E9pHhQe65hNGoy17B7xDfeazWbE9IvSk2cQCSiAJIk4e1jR7Dr1LGAybxiUcSDixthKygICCg9/Q5V13V6PHjr6CEIOTl46+ihkJ/zvETSKy8nF2PXxyP+PHhiWm09+Ei7bv2fHy6066n7zrJcRESZTel8kbqpVei+fAk9ly7CazKhdnI5ZpRVhHwJ919d3O3oY3aiuHvtUDsEweTLJpGykRrR8pMgCKoz1PEL59B2KvR8bOYpIiLKBp29dmw9sDdgR1ixVcT6pcvD3me9ksTcmAG+WL/IsHyjddzK9dmYmtL4GitDZC5OIBKRT2evHb9u3+W7MfgbcDqxede7AY8ViyIeXNKoeufg28eORG1jzTdjZGwUXq9Xfccpqz20bAUseXkRJ/r01oMHlOvJRxoMXl47S/fv4l+Wi4iIMkO080Xyc3MxOv75Qph3AIj5Zsy7rQr5OTnwmkyYdkspSiZM0DzRQhSLcBNywdnoytAA3j99KmBgskS04YEly2CzFKjOT+sblqs+O6fDfkbx58xTRESUqSLmSteNe3bT7Hk4ct4eMLlozVfePUbpYXJRsWHX0nteYV5OLp5oXoNP3SOq8x0XdaU/TiASZTB59ceAcxhDLhecox4IAGrKb0Xt5PKAL9WRQoiSAacTm3e+i4VV1fjAoHPqXKMeNEyvRcfZbkOuR5nP6XFjac1MxYlCrfXg/YWrJ680GPzm0cO6y/HKZbli6S8RESVHuFW34+PjeGnvTsXn+U8eypyjHhzoOe378/s4CUD7RAuREYIn5IKz0RfqFqparBVtMv3xu9dEPYPaZrFg2K189ifzFBERZaLx8XG8+H6bYptwO/RdozwqKBPI+V/vTj//59kKrFHPNQxnwOWESRCwqHqG77Fo+Y6VIdIfJxCJMlS41R8+x47AajZjQ+Mq3zbzaIfnKjnbfxnWfLNhocSSl2fIdSg7TLAUANB3cLQe6j4vJt3X564SIqL0Ey53mfPy4BkbM/R1tEy0EBkl2oScmgymJj+9fnAfHlzcGFL1xF+4CfdwmKeIiCiTdPba8as9O+BReR+kzGIymVA9sVT3Tr9wz4t2rmEk/hlLTb5jZYj0x785ogwkr/5QGlRyeTzY1LYNnb12VYfnKhlwOXH3nDrdzw92S2GRYdeizFcs2hL6emo+L06PG+vmL0axqH2HCHeVEBGll0i5y+jJQ3/yRItR7rp9DmbfOsWw61HmiXVCTk1+uuYchq2gABubmiFGGNRSO4HIPEVERJlCzpqcPMxeXq8X7544GvY7h7zA8Mi5s2GfG+m7iv+5hlr4Zyy1+a6n36HpNSi1cAKRKE2Mj49jx8kuvLp/D3ac7MJ4hOCgdTfh1gN7MeAcjrl/Ix7lUkJq2SwFuGvGLNgsFkOuR4lnAlBeXJKQ1yoRbagpLUvIa8nUDqCVFhbhhw88AlHDezkZvw8REUUnSRK6HX04bD+DbkcfJEmCJEn46NJFbGnflfD+qJloUctkMuH9j07i1MVPDOodZaJYJ+TU5qchlxN1U6uQm5Oj+7WYp4iIKFOMjo5GLYevRV4M91dKrnDlaf09v/s9HDkfOImoZoz4xrmG9+NrK1ZHHb8Kzlha8h2lL5YwJUoDvz20DztOHoPX6/V7bD9Wz6nDlxcvC2h7xtGnaTfhgMuJT90jMfexw34m5msAwLB7BH/z/72CqomlOPHJBUOuSYl1680T8f37H8D3t76IQZcrrq+1rHYWjpw/q6nue6zUDqAVWkXYr/bDGeWcHn8tDY0s60BElARKZ4lEKvljAnSdd2uUIZcTC6qm49Wc92O6jn++JArHiAk5Lfmpp98RU4ZkniIionQnSf//9u49Psr6zvv/eyYJM8mEJIgQknAKIYSDEJCzBAURxVPbe1XoQdra1mXv2u5at3v3ru1937vdWrd772/bPdxr1XVtlW3V6vZgqyhnDYocDGcJMRCQECJaSMiEBMI1vz900hzmcM3xumbm9Xw8fDya4ZprvtNrDu/5Hj5fQ09sWT9oQChWPsMnj8tlaYZFdDrDXDOfz6fHN70i5zJHbzlTMysE/fsazp9YpSHZ2QH3M/QbmLEiyXdIXQwgAjb3wo5tWr9/z6DbfT5f7+3+QcS6pkY9HcUs+I6uLrlzctQVZamt3CFDIhokCeec18uePinsvQ/PqO74UX164bUhg0csXDk5ckj63ds7em8zU/c9HiqLS8LuO+XvaDMb9j0ul+7+eE9SAEByhdpLRFLA77JwP+CTYag7N+aBFsCMeAzIJSo/9e0AHebJ18oFNeQpAEBKq2tq1JNbN5gu2x2JHp+hHhvkWEQmkkHfvnsORrpCcNb4Cq1ZtmLQb6NgGSuSfIfUxQAiYGMflS3dG/KYDQf26pNXz9f+k8ejHqxZt3d3VPfzG1lQqOMfnInpHEgvv3hjq/7+M/dozbIVWlu7OW6z21zZ2boif6hazp0d9G/+uu9rlq1IaMeR0+nUqgWLTc3KMjvL6ivXr9CU0tHxaiIAwCT/niAD+b9TYi0PmkiPb35F44aPsLoZsEAsE/+skqj85HQ4Aq4cBgAgFQXLpshsZVcM15GWU6aO9e85WFVSFtUKwVnjK1Q9tjxodZa+Isl3SF0MIAI2tuXwgbBlpXw+nzYf2q+Nh0IPNCZKttPJ4CEG6ejqUkNri6rHlkdVWm1+xSQNzx+qy4ahEx9+oMbWU7p4+bK6e3oCDh721Xe2VaKYnZVldjZW1ajShLUVABCYmT1B7FzeydvdrUOnTlrdDFgg0ozjys7W0mnVcuqjvao3HtoX0QDk2totcclWichPdEgBANKFmWyKzGR28NDPv6Iw2hWCTqdTVSVlph4r0lWLSD0MIAI29kF7m6nj3n0/fE3rePPPfO4xjKQ+LlJHe6c36tJqb8Wwp2bf2VaJZGZWFrOxAMC+zOwJAthJvjtXS6ZO71fC3YzLPl9MFUe83V060tKsyWVjoj6HH/kJAIDAyKaIF/+KwmRlqkhWLSL1MIAI2NiVBYWmjnNn5yS4JR9ZXDVVE0eVqjA3T0++tiHlSichudoudKqxtcWSxzZb5z1WZmZlMRsLAOwpWd8V0Vgx42qd9XboTHubjp5ptbo5sIGcrCzds2S5Oi5EPjGr5/LlmB+//vSpuAwgSuQnAAACsXM2RWJEsrehWQNXFCYrU0WyahGphQFEwMaWTL5KL+x4I2QZU4fDoXmVk2NasWXW7qZGTR09Vg6nM6pVZcgsz7+1zbLHNlvnPVmYjQUA9pOo7wpXTo66Y5xktW7f23FqDdLFpcuX9S/rfitXTnImDg7kCLOtQiKQnwAAmcRu/RhIrDvnL1LZFVfqn17+TVzPG2hFIZkKsWAAEbCx7Oxs3XBVtdbv3xP0mBuuqtaUkrKwNa3jobO7W49uXKdl02Yk9HGAWOS73YPqt9sBs7EAwF7M7Anicbnl7e6K6Lw+I/kDLcgcsQ5OR2uiRfs1k58AAJnCTDZFehjmydf1U2fIMAw5HI6QC0ciOWeoFYVkKkSLYWbA5u6Yt0jLp8+Uw+Hod7vD4dDy6TN1x7xFvTWtkyUZqx2BaF03ZTqzqAAAYZnJT3fXLNGaZStU5Ok/I9zjcsvjcvW7zZ/ULl7uiWczAVtwkK0AAEioZPftwTr+VYKNZ1rjMng4b0KlHlq5mhLvSAhWIAIp4I55i/TJq+dry+ED+qC9TVcWFGrJ5KuUnf3Ht3CwmtaJ0NHVJYck5tfDjkYVFlndBABAijC7J0igkj+S1NDaon3Hj2rjwX3kIqS1aPZeBAAAkZk1vkLLp88MWYkMqcvjcuvumiW9vzHite/lwqqpTKRHwjCACKSIj8qZzgx5TN+a1nuajmrzoX0Jaw+dZLAr9g0AgMAMw2DfiwDM7AkSrORPZXGJnty6PpnNBSxBvgIAIPEMw9AOqn6lpXkTKvXF627o9xsjHvnK43KryqJS88gMDCACacbpdKqyuESPbVpndVOApBvmybfl/ocAYLW6psZBq+yKPB6tWrCYUjeKfk+QhtYW9qlB2iNfAQCQHA2tLWrrZNV/OjrfdaHf4KFhGDJ8PnlcLnm7u6M+7901S5gUioRiABFIQw2tLfJ2dVndDCDp/HXkAQB/VNfUqEc3Dp5YdM7r1aMb12nNshUMIkYpXmWHADsjXwEAkBxky/R1pOWUDMOQ0+kMOLkzUkV5Hq1ayGRQJB4DiEAaInAgXbhzctR16VLY4/LdufrcousITgAwgGEYenb76yGPeW57rarHljNAEAXKOiKdDdwLFAAAJBbZMn1d9n20nURnd1fAyZ2RuHP+Il0/dUZEv9/YzgLRYgARSEMEDqS6JVOna9b4Cp3zdujJrRvCHn/X/EV0bgFAAGZKbJ71dqihtSWqEp6ZrrK4REUeD2VMYXvTRo/RwZPvmT7+lurZuu3qeXQsAQCQRJXFJTGXtIR9nfN26Fe73oz5PIW5eRFlNLazQCz4NQCkIX9nFmClO+cv0peXLNc3bvmU7r3+pojuu+XQfnV2d6nIk2/q+A/Ot0XTRABIe2arElC9IDpOp1OrFiy2uhnIcK7s8POCIxk8lKSqsjEMHgIAkGROp1OfvWaJ1c1AgpzvuhCXiYeRLBzxb2cx8HH921nUNTXG3B6kN34RAGmIzixYLd+dqyWTr9LcikmqKinTrHETtLByckTneG57rSpGFKvIRDB6/fAhGYYRbXMBIG2Z/XFJ9YLozRpfoTXLVjB5C5bp7umJ6/mGefJVWVwS13MCAABzZk+YqOXTZ1rdDCSAx+WO+RyR5DSz21nQn4ZQKGEKpCl/Z1asm/IC0ejouqDvPr+2dyA7mtfhWW+HGs+0qmbyNP3u7R0hjz3X6aX8HgAEYKbEJoMFsZs1vkLVY8s/Lhnbocb3T+u1dw5Y3SwgKisX1LD6EAAAC90xb5F8Pp82HNhrdVMQR97urpjPEUlOYzsLxAMDiEAa69uZte/4UW08uM/qJiGD+MshxKK906vigkLTxwIA+vNXJQj1ecxgQXw4nc7eH95zJ1Rq99EG9q9BXA3JytbFy/FdbdjXME++Vi6oYS8cAAAsVtfUyOBhGhrqzjU1ufPOeYv08ze2DPotkedyRfR4bGeBeKCnAEhzTqdTlcUl2k1NaySAx+VSdgI7nQvyPHq//ZzpYwEAgwUrsTnMk681y1YwWJAATqdTS6dVW90MpJns7KyEnv/O+Yv4PAAAwEKGYeidUye1tnaz1U1BAhR58sNuOfXR5E5HwImInd3dEe1byHYWiAdWIAIZwMySdcCsLKdT102epurxFTJ8Pv3Ty79JyOO4c3JUPnyE/mPLq2GPpfweAITWtypBe6dXBXkeVRaXsPIwgUqKhlndBKSRhZWT9WbD4YQ+xvNvbVP1mPFqPNPK5wQAAElW19TINkRpzN9v5XQ6A2455a8EUT22XA8+91TIcz23vVbVY8vDZjS2s0A8MIAIpCjDMEx3ArIUHfF02TBUWVKmqpIy7Ww8krDH6bp0Sd/+5dPydoWvEb+oaiqdWwAQRt8Sm4hNuBxW19Soxze9YmELkW5c2Yn/6X7W26FvPfuzftmryOPRqgWLWZkIAEAC1TU1xrwFDOxtUdVU7T72rgryPKoeWx50cmd9S3Pc9i1kOwvEAwOIQAoKNCupyOPRXfNqlOd2q+HUSfkcDlWNKtWkkjKWoiPu/LOdEv3aMjN4KMn0PokAAMQqUA7Ld7lVWVKmksIiVZSU6dk3X7ewhUhHV0aQdRwOh3w+X1SPMzB7+fe0ptwxAACJYRiGnt1OdkxXHpdbPvn0u7d39N4WaoJWvPct9G9nEWzFI/kO4TCACKSYYLOSznm9enxz/5nuL+ujPeo+u2iJPC5XwPrZQDT8s53MlENIBgbJAQDJECyHdXR3qa6pUXWStHd30tuF9OZwOFSY5zGduZZNm6ENB/bGtQ1mS2UBAIDIsO1Q+rp6fIXeDrBfYagJWkPduabObfY4ie0sEBsGEIEUEs2sJG93NyW0kBDtnV45nU7NnVCp9fv3RHUOd84QdV26GFM7oq3XHkkZYAAAmB0Oq/h8Pj2x+VXdcNVMbTiwJ+hxHpdbS6ZO15ZD++LehlClsshUAABEj22H0tMNV83UrmMNIY95bnutpo8ep4b3T6vh1EkZkrwXLpg6v8/hiKg9bGeBaDGACKQQZiXBToa6c2UYhnYeDR2IXNk5uni5J2Apra5LF+XKyVH3pUtRt2POhIkRd1IFKwPMHj8AgGDIYbDaxoOBVxV6XC5NLh2td1tb9Pu6nQl7/EAdnGQqAACiZxiG2i50Wt0MxJE7J0erF1+vfHduyIlf0kcTtP7y5/8RVZ9YB68bJAnTAoEUwqwk2MmTr23Qy3t3he1M7e65FHIfnlgGDyVp/f49qgtQEiIYf/m5ge32l5CI5FwAgMxBDoPVguWphZWTtftYo9o6E9uRNLBkPJkKAIDo1TU16sHnntLzb22zuimIk0nFpfrHu7+i2eUTTf92iLZPrCDPI8MwVN/SrJ2NR1Tf0izDMKI6FxAKKxCBFMI+b7CTts5Ovfh24ma5R8Lsvjxmys+xxw8AIBByGOxq48H4lywdaGDJeDIVAADRC7avNlJbefGo3rLuB5vfS9jjDPPkq6Prgh587imqQCDhSPJACqksLlGRh84rYCD/vjzhmCk/Z/ZcAIDMQg6DXYWq9BAvKxfU9BsIJFMBABAd9tVOX5sO7tWPXvq1ntiyXtsbDifsceZMmKjHN71CFQgkBQOIQApxOp1atWCx1c0AbMlMeQizJSQoUwcAGIgchkw0zJOvNctWDJrJTqYCACA67Kudvi5dvpzQ8w/z5OvepTdp59GGkMc9t72WcqaIGwYQgRQza3yF1ixbwQx4YAAzpeXMlp+jTB0AIBB/Dst3u61uCpAUd85fFLAMFpkKAIDoMLkG0bhz/iI9tHK18nNzqQKBpGIPRCAFzRpfoeqx5b11tQvyPOrouqCnX9+krig33wViceusudp25JBls+g8Lpd8hiHDMELus+MvPxeqnQP3+AEAoK9Z4yt0sadHT27dYHVTAEmSQ1Kiipg+/9Y2zRo3YVC+IlMBABAdJtcgUsM8+bp+6gw5nU6qQCDpWIEIpCin06mqkjLNrZikqpIyzRo3QddNmW51s5ChttUf0l3zavSNWz6lm2fOSfrje7u79eN1v9WDzz0Vsta7mfJzA/f4AQBgIDp+kEgOh0O3zZxjOlNdXT4x5L/nuVxRtyXYDHYyFQAA0WFfbUSqb6aiCgSSjTQPpIG6pkb91c//Q6/se9vqpiBDnev06vHNr6izu0u3z5prWRg2s2F0sDLAwfb4AQBgIIcvUeu9AMnn8+l3e3ap6+JFecKUy/W43PrykuUhs83qmqUxtSfYDHYyFQAAkXM6nZo7odLqZsAGlk2bEXKiV6BMVVlcosK8vJDnpQoE4okSpkCKq2tq1KMb11ndDEDSRxs1V48t16oFi+P2usx3u9XR1dX7t8flUs9lQ909wcv1+tsRbNZ7oDLAlcUlzJIHAJhyvuuC1U1ABth8aF/YY+6uWSKn0xk226xZtkLPbn+9X8lRj8stb3dXsFP3ys8N3klFpgIAIDJ1TY1av3+P1c2ADcwYN0F3zFuk+tOn1HDqpAxJniEuFeTlqejjQcCBmWrviWPquXw55HmpAoF4YgARSGGGYejZN1+3uhlAL3+ZK/+M9IEdVZEa5snX3975OTWeae3tlPIZhn687rem2lFVUhb0GH8ZYAAAIjXUnWt1E5DhhnnytXJBTb8Z6aGyTaCBvsuXL+ufX3kx7GOFW3FLpgIAwBzDMPTsdvrx8MdVgk6nU1NKR2tK6eiw9wm3iMTjcuvumiVUgUBcMYAIpLCG1hadY1NcJNi8ikna0XjE9PH+Mlf+jqr606f075vWydvdHfFjr1xQo+zs7H6dUjtNtoUNowEAifJu6ymrm4AMlO/O1V3zFwWdkR7OwIE+s5mKFbcAAMRHQ2tLTJOskT4iXSVoZvB5SHa2qseWx9o0oB/WsgIp7Jy3w+omIANcmT80ouP7btTsdDrldDgiHjwMtXcOG0YDAKxkGAZlp2CJjq4LKvLkq6qkLC5lqchUAAAkFxOdke92R7VXtJnBZ381LiCeWIEIpDBmAyMZKktHq+jdw6ZmyQXaqNlsQL555hyVFg0Lu3dOZXGJijyekO1hw2gAQKIcaWlWd0+P1c1Airp11lxtO3Io6tUH8ex4JFMBAJBcTMpJX3lDhqjz4sWQx+S7c/V3qz6v7OzIh2TMZkAGqRFvrEAEUhj77yDRhnnyVTWqVKsWLDZ1fKASDGYD8uTS0ZpbMSnsrHqn0xm2PWwYDQBIBMMw9EbDYaubgRRVlOfRrTPnmM5VgcSz45FMBQBAcvkn7yB9+CtorV58fdhjP7fouqgGDyUqR8A6rEAEbMAwDDW0tqi90xt29VVfRZ78JLQOmczfaTRrfIXWLFuhZ7e/HnCW+jBPvlYuqAlYgiGes9v975Wey5d129XzVHv4YL99QEO1AwCAviLNX3VNjUG/BwEzVi1cbCpXBRPP1YBkKgAAEi9Q3ly1YLEe3bjO6qYhBiuqr1bZsOGDfkOsWbZCT9duVueAbXw8LrfurlkSU66KV99atH3QyFwMIAIWC9QZVeTxaNWCxWG/WCpGFMshyZfgNiIz3Xb1vH6vwVnjK1Q9tvzjuusdOt91QUPduSr6OKAECxz+2e2hArKZ2e2B3iuFeXm6/eq5GllQRPABAJgWaf6qa2qkowcxMZOrPjx/XpsP7Qt6jnitBiRTAQCQeKHy5r1Lb9K/b3lVPh89eqko352ruRWTBt3uz3f1p0+p4dRJ+RwOVY0q1aQ47F8dj761WPqgkbkcPj6pEqa9vV2FhYVqa2tTQUGB1c2BDYXrjPJvqmsYRsAvn4bWFv3opV8nr8HIGHlDXPqHz30prh1HgYKK2dntZt8rQKLwnW4vXA/Ewux3Sk9Pj7YcPqAzbee042iDLoTZ0wQI5d7rb9Ls8olhj4slL5lBpoId8b1uL1wPIHbhvm9vv3quXnx7ZxJbhHi657obNH9ilSWPHW1WJANmrli/11mBCFjEMAw9u/31kMc8t71Whs+n/9y2pd/y95cleVwulY8YleBWIlM5HI64n7PvTPtISiWYfa9Ujy1npjwAICSz3ymNrS3aeHAfs8IRN8+/tU2zxk0Im1WizUtmkKkAAEg8M9+3mw4GrzgA+7NyS6losiIZELFgABGwyEflikLveXLW26HHN70S8N+83d06cPJ4IpoGyNvdpZf37tKts+bF9bxOp1NVJWUR3cfse6WhtSXicwMAMovZ75QNB/YmqUXIFJFklWjykhlkKgAAEs/M9613wB55SB3x3JM6WpFmRTIgYsGQMmCR9s7QH9yA1V58e6fqmhpDHmMYhupbmrWz8YjqW5plGEbc22H2vcJ7CgAQDt8VsNK+40ctfXwyFQAAicf3aGqbMXZ8yH+P157UyUQGRCxYgQhYpCDPY3UTgLCe216r6aPHqfFM66DSCMnafNnse4X3FAAgHL4rYKW3Go/ojnmLLOt0IlMBAJB4fI+mLoekfSeagv77DVfNlHuIS7/dtV0+h0NVo0o1qaTM9gOKZEDEggFE2J5hGAnZA8RqlcUlKvJ4wi4hB6x01tuhbz37M3m7unpvK/J4NHdCpdbv3zPo+HNerx7duE63XT1Pt1TPjuq9OvA9XzGiOOx7xQ4lJAAgnZC/gPjr6Iq8RHws70UyFQAgHaRaLiVvpq5wu59vPLBHGw7s6f37ZUkel0t31yztN5E+Ea/ZWM5p5jVJBkQwDCDC1uK9winUh22yA4nT6dSqBYv16MZ1CXsMIB76Dh5KHw0SBho87Ot3b+/Q64cP6NMLr43ovRrsPR9swNIvFUtIAIBdRZq/IslQVncAkb9gtRff3qnSYcNN5aNYfguRqQAA6SDa78JgmTMZWZS8mb4CDTB6u7v16MZ1WrNshWaNr4hbX3bf12pre5tqDx/Uuc7ozmnmNUkGRDAOn88XbnAdUWpvb1dhYaHa2tpUUFBgdXNSTl1TY8gPNv8HcyTnC/YBLikppRjNtmuYJ193zF2of9+yPqGPDSSD2fdquPf88ukztfNow6D3ysoFNQl/nwJ8p9sL1yNxIs1fkfxATlbpazOC5a+uSxd14eLFpLYFmcfjcuv/fvYeSQraiRnLbyEyFVIN3+v2wvWAXUT7XRhqEs3A779EZtFA7XDn5Kjr0qW4PxasN8yTrzvnL9Ljm14Jekyg12ygQe29J44Neu1Ecs5ggv0GIgOmt1i/1xlATCBCV/QMw9CDzz0Vdmn1QytXB5wdMfDDt+PCBT2+OfgHeCiRDlRGwzAMHWlpVv3pU3L4fKosHS2fYeifX3kxoY8LJEOo96qf2ff83975uYD7MQKJxne6vXA9EiPS/BWuU+fepTcpPze3d9bs797eEfLY2RMmxtT+SPX09GjL4QP6oL1NVxYUqrToCrIXkmZ2eYUa3z8dsBOzemx51L+FyFRIRXyv2wvXA3YQbb9guHwaTLz6/gb271WUlClL0v73mrS98cigCk9IL+EGiAe+ZgMN6OW5XOrs7jb9mGb63PqyuiIMki/W73VKmMKWGlpbws6yOOvtUENri6pKyvrdHujD1+FwRN2W57bXqnpseUI/TAfNLNm7O2GPBSRbsPdqX2bf841nWkOeBwAQvUjyV2VxiZ7d/nrIY/99y6syO1fx37e8Kjmk2eXJGUQM9mMdSJbdxxoH3ebfS/r2q+dG/VuITAUASAfR9AsahhE2nwYTj76/uqZGra3dLG/fwZ+9uzUkO1sXe3qiPi9SR7jVpX1fs8EGuyMZPBx4TjOcTicZEBFhABG21N4Zfol2oOOCffjGstA20g/iSEU7OwpIJeHe09G+5wEA8RPJZ7GZTp1I8pfP59Pjm16Rc5kjKeXj4/FjHUiUTQf3mTou0HuWTAUASAfRfJ+ZyafBRNr3F0nlMwYP0Vd7pzemwe5g5wQShQFE2FJBnifi4+L94dtXoj6IE9lmwE7Cvaejec8DAOIrks/iRGWjRFd+IHshFXhNDmYHes+SqQAA6SCa77Nz3o6YHtPs/eNd+QyZZag7N6bB7kDIdUgkCtzCliqLS1TkCf3hN8yTr8rikt6/4/3h21eiPogT2WbALtw5Q/q9VwOJ5j0PAIivSD6LE5WN/LO/E4XshXQRLBeRqQAA6SCa77PzXRdiekwz9/dXshiYJ2OpfIbM8uRrG7Tv+NG4nY9ch0RjABG25HQ6tWrB4pDHrFxQ0292eqJmwifygziWNk8tGxPHlgCJ4zQxEy+a9zwAIL4i+Sw206kTrUSW4KG8D9JFsFxEpgIApINovs+GunNjesxw96eSBeKhrbNTG02WqzeDXBd/hmGovqVZOxuPqL6lWYZhWN0kS/Hqgm3NGl+hNctWDOqcGubJ15plKwbtj5OomfCJ/CCOpc2Hmt+LY0tgR3lDXPqTuQutboYk6far5+qe626Qx+2O+L6dF7tNrSaJ9D0PAIg/s5/FZjp1opXIEjyU90E6uO3qeSFzEZkKAJAOIv0+K/Lkx/R44e5PJQvEU6xlb8l1iVHX1KgHn3tKP3rp13piy3r96KVf68HnnlJdU6PVTbMMeyDC1maNr1D12PJ+GxNXFpcEHNDzz4QP9WXucDhMlxVwOBz6ypIbE/pBbKbNyFyLqqZo48G9lrbBIekrS2/S7AkTJUlDsrP16MZ1EZ/H7IqPSN7zAIDEMPtZ7O/UGbgHTCwSXYKH7AWreVxuXTNpstbv3xP1OYoLCsMeQ6YCAKSDePcLBmMmg1LJAvEUrn/a43L12xe7KM+jxZOnamRBEbkuQfwligc65/Xq0Y3rMnbAlgFE2J7T6VRVSZmp41YtWBxycOMrS29UvjtX7Z1evd9+Ti++vTPksbPLJ0bVZrPMtBmZ6YarZsbUsRQvX7n+pn7vA39n8drazf2CTDiRrPgw+54HACSO2c9if6fOkZZmPbb5FXVG8N0QSKJL8JC9YJWKkaN0+9XzNKmkTE6nUxNGjho0+J7vzlWHif2XzOYqMhUAIB3Es18wGDMZlEoWiLdl02Zod1Njvzw4zJOvlQtqmAiWZGZKFD+3vVbVY8sz7jowgIi0EmwmvP/Dd+AsgdJhw00fm+w2I7O9+e5hq5uge5feFHAQvXpsuZ7Jes30edjQGQDSm9PplMPpNDV4eNvV81Q27ApL8xfZC/GUO2SILly8GPa422bP1+TS0b1/B1pRUTGiWN99fm3I1yW5CgCA4EL1C86ZMFE7jzZEnUGpZIGBPC63fPL1+x00zJOvRVVT9bu3d4S9/4xxE3THvEVBBwqZCJY8ZkoUn/V2qKG1JeOuCwOISDuRlDewS2mfge0ItzoS6c/b1WXp4987YOWhYRi9r8+2C51q6+w0fS42dAaA9Ge2pFNxQaEt8lffNhw+dVIv79mVtMdG+hjmydff/Mln9FfP/FTdly4FPc7jcqtqVOmg251OpyqLS3rfC41nWnXXvBo9vvmVoOciVwEAEFqorPnf5iyMOoNSyQJ+y6bN0IxxE3ondQ18TUlSbf1BU5PCqBhhD2Z/z2ZiKWMGEJGWIvnwtcsH9cB2dF26ZIsSlsgsHpdbd9cs6Tf7rq6pMapVGh6XS3fXLM3I+uAAkGnMlnTyH2eH/OVvQ2Vxid5seIfZ5IjYygU1GjJkiL547bKQnYl31ywJ2DkZKGMVeTxaPn1mTCskAADIdMGyZqwZlEoWkAa/jvz/u+/k+5qqaSFXITIpzF4i/T2bSRhABGzIMAztPNpgdTNgEbP73wTjcbll+AxT5bT8XNk5unHGTN1cPadfgAm2gbAZX7l+hab0KdUFAEhfZko62bX0IrPJ059Dki/O57th+szewTx/Z+Izb77Wr0pDUZ5Hd82vUZ7LrZ2NR/qtdAiWsc55vVq/f4/uvf6m3r3b2fcGAAD7GLjCcag7V0++tiGiSk1Ibev379Gooit05dCCftlu4MBynsslhyTvgBKnTAqzn1T+PZtoDCACNmSm7jLS14KJVdp1rCHq14C3O/Lyp909l1Q6bHi/jikzGwgHM8yTH7BUFwAgPZkZhLPzLFv/ANB/btuiDovLiCP+4jl46D/f+v17NGHkqH6DiNVjy3WkpVn1p0/J4fPJ4XTql2/V6lxn/xWGd82v0S/fqg35GM+/tU0PrVxt2/cMAACZbOAKtE8vvJbJaBnm6dc3Sfoo282dUBmwipx/b8Tbr56rkQVFTAqzsVT/PZtIKfWMH374Yc2dO1dDhw7VyJEj9alPfUr19fX9jvH5fPrrv/5rlZaWKjc3V0uWLNHBgwf7HdPd3a2vf/3ruvLKK+XxePSJT3xCJ0+e7HfM2bNntXr1ahUWFqqwsFCrV6/WuXPnEv0UYVOGYai+pVk7G4+ovqVZhmEk9HHqjr2bkPMjNbzZcFh3zatJ+uM+t72232s7loHsTP1SBVIZOQux8g/CFXn6l3UZ5snXmmUropplm6wMJknVY8u1aNLUhJ0f6efZN1/v95rce+KYfvr6Rr28Z5de2rtbv6/b2W/wUPpoheHjm14Jm7HOejvU0NqSkHYDSD5yFpBaIs2gwXJwvjs3kc2EDfirR4RSW/+OZpdPVFVJGX1lNpaI37PpIKVWIG7dulX33Xef5s6dq56eHn3nO9/RjTfeqEOHDsnz8YX9+7//e/3jP/6jfvrTn2rSpEn6/ve/r+XLl6u+vl5Dhw6VJN1///168cUX9cwzz2j48OH6y7/8S912223avXu3srKyJEmf/exndfLkSa1b99Go85/+6Z9q9erVevHFF6158rBMsL1JVi1YHNcPjmj3mUP68XZ36XTbH3Tb1fNC1kuPN39HlX8W3b7jRyM+B6UYgNRFzkI8DCzpFMss22RlsGCPBYRzrtPbm51iKfseTHsnr0cgXZCzgNQRbQYNlIPPeTv05NYNyWg2bGxgfxvsK56/Z9OFw+fzxbuiS9KcOXNGI0eO1NatW3XttdfK5/OptLRU999/v771rW9J+mh2VnFxsX74wx9qzZo1amtr04gRI/T0009r1apVkqRTp05pzJgxeumll3TTTTfpnXfe0dSpU7V9+3bNnz9fkrR9+3YtXLhQhw8fVlVVlan2tbe3q7CwUG1tbSooKEjM/wlIqHAdAfGafZCIDgekNo/LpR9++ov6zi+fTmod/S8vWa65FZNkGIb+6hdPyhtBGbc75y/S9VNnZPSXKtJXJn6n2zlnZeL1yDTJymBmHgsI5ctLlmt2+UQ9+NxTcR+A/sYtn6KjCRkhE7/XyVmAPcUjgxqG0Tv4cLD5PW1vOBzvZiIF+fvbgGSL9Xs9pXt529raJElXXHGFJOnYsWM6ffq0brzxxt5jXC6XrrvuOr3xxhuSpN27d+vSpUv9jiktLdVVV13Ve8ybb76pwsLC3rAlSQsWLFBhYWHvMUh/ZvZ/G1jyMVGPg8zj7e5W45lWfXrhtUl93IK8j2a/NrS2RDR4KEmFuXkMHgJphJwFqyQrg0lST0+P/nPblpjPg8xVkOdJyP7lwzz5qiwuies5AdgHOQuwn3hk0LqmRj347FP60Uu/1hNb1jN4iF7+/jYg1aRUCdO+fD6fHnjgAdXU1Oiqq66SJJ0+fVqSVFxc3O/Y4uJiHT9+vPeYIUOGaNiwYYOO8d//9OnTGjly5KDHHDlyZO8xgXR3d6v7481RpY9Gd5E4fWf0JGI5sZmOAP8S9Mrikn5tqRhRrMYzrabalogOB6SH9k6v5lZM0pplK5JSVq1vR1U0JbMIQ0D6sFvOImPZR6Lzl2Q+gx1padbksjFRt62uqVFrt22JeMIM4Ff08etsdwL2L2c/aSB9kbOA6CUyix5paTaVQTcd2qfC3LxBj09VCwTDxDCkspQdQPza176mffv2qba2dtC/ORyOfn/7fL5Btw008JhAx4c7z8MPP6y/+Zu/Cdd0xEEy9sQxO4Cy7/hRPbl1fb+2OBwO9a0OHKpt0ewzh8zgH5Dz198+0tKsf9vwki729CTk8fp2VEU6GEgYAtKL3XIWGcsekrUnodkM9tjmV7S6Zqlmja+IuG108CAeVi1cLKfTGdUkqmGefN05b5F+uaO23+uW/aSB9EfOAqKTyCxa19Sop2s3mzr2+be2DXr86rHlWmvy/sg8TAxDKkvJV+7Xv/51/fa3v9XmzZs1evTo3ttHjRolSYNmVb3//vu9s7hGjRqlixcv6uzZsyGPaW1tHfS4Z86cGTQbrK9vf/vbamtr6/3vvffei+4JIiR/h8/AWUHnvF49unGd6poa4/I4ZjsCNh7cN6gtA7cWDdY2wzC0vfFIbA1FWho4IOd0OjW5bIzuue6GhDzWwDr+lcUlKvKY7wwjDAHpw445i4xlvWTlL8l8Buvs7tajG9fphR3bImob5eMRjsflNnVM9dhySZHnJumj7DR7wkT9YOXn9Y1bPqUvL1mub9zyKT20cjWDh0AaI2cB0UlkFvWfu7PPSlyz/I//+z275I3i/rCfcJM2glk+feagPBiovw1INSnV2+vz+fS1r31N//Vf/6VNmzapvLy837+Xl5dr1KhRWr9+fe9tFy9e1NatW3XNNddIkmbPnq2cnJx+x7S0tOjAgQO9xyxcuFBtbW3asWNH7zFvvfWW2traeo8JxOVyqaCgoN9/iK9k7okTTUdAOAPbFs0+c8gMi6qmBhyQmzW+QmuWrVDekCFRn/uOedfo/hWfCNlR5XQ6tWrB4rDnIgwB6cPOOYuMZa1k5i8p8gy2Yf+ekP8eKH9RPh4DuXNytGzaDH3jlk/pK9ffFPZ4b3eXGlpbJJnPTdLg7OR0OlVVUqa5FZNUVVLGhCwgTZGzgOglMovGa2LZhgN7Yj4H7OFLH/eV3XPdDbpz/iLdc90Nuv3quSrMywt4vD/b3TFvERPDkJZSqoTpfffdp5///Of6zW9+o6FDh/bOzCosLFRubq4cDofuv/9+/eAHP1BlZaUqKyv1gx/8QHl5efrsZz/be+yXv/xl/eVf/qWGDx+uK664Qt/85jc1ffp03XDDRyt7pkyZohUrVujee+/Vo48+Kkn60z/9U912222qqqqy5slDhmFo06HBq/0G8u9LWFVSFtPj+TsC4lneyr9fj8PpVHunV6fOnQ1/J2Sk4oLCoP9WPbZcz2RnSxcvRnXuojxPvz2jgvEPVg4sEZLvdmt+xSTNGDchIXtfAbAGOQvBmN0PJh75S4o8g/nC/Dv5C325c3LUdelS798el0vXT5uhm6vn9GaanSYrhPQttxssNxXlebR48lSNLChK2L6hAOyPnAW7SMZ+1vFmdn/saLJovCaWdffJFkht/7XjDT20cvWg98XN1XM+fr106HzXBQ1156ro4+ph/mP9E8OAdJJSA4iPPPKIJGnJkiX9bn/yySf1xS9+UZL0P/7H/9CFCxf01a9+VWfPntX8+fP16quvaujQob3H/+hHP1J2drZWrlypCxcuaNmyZfrpT3+qrKys3mP+8z//U3/+53+uG2+8UZL0iU98Qv/6r/+a2CeIoALVOQ/F7N454QTrCBi4x2EkHtv8SlRlEZBZWs7+QYeb35PP4VDHhc5+wb6htUVtnZ1RnzuSfXr8+y+m2g8MAJEjZyGQSPaDiVf+kv6YwdbWbo5LOSjyF/zuXXazsj8eTA6Wa8xmpYHHkZsABEPOgh0kaz/reDObMfcdPxrx4M05b0c0TUIaCzYYzeAgMpXDF+0oCMJqb29XYWGh2traKAERA38t8kh845ZPxfVDve8MrbYLnf02TAaSxR/sey5f1hNb1oe/QwDDPPkBZ1IBCI3vdHvheiRHpBks3vlLkt45dVL/9PJv4npOZLYvL7lRcysqQx5jGIYefO6pkJMXyVRA/PC9bi9cj/QULtfZeWuS+pZm/eilX5s6NtLnseHAHvr4MMiXlyzX3IpJVjcDiItYv9f5tQNbi6YW+bCPl49H+3j1Lc3a2XhE9S3NvfXT++5NUpgbuOY1kGj+zbnfbz8X9TlWLqihowsAEFakGSyW/OV/vEAZrGpUqfKGuKI+LzDQE1te1Qs7QncUmtnTkEwFAEgVyd7POt4i2R870ufhcbmjbRbSWCSVu4B0l1IlTJF5oqlFHu2PebOlHPgSgdVeP3xIRXkenQtRxsOh/ntCDfPka+WCGtvOKAQA2EukGSyWwZRwGax6XLnebDgc1bmBQNbv36PxI4o1u3xi0GOCbWVApgIApJpE7iGYDJHsjx3J86hratTzYSYVIX0U5Xl01/wa/XJHbdgqE5XFJSm5XyiQCAwgwtYi2Usn352r+RWVynO5ZRhGRB/qwUo5+Fd89S2BUFlcIo/LFZf9eABJys7KUs/ly6aPP9fp1W1Xz9Pv3t4R9Ji+g4cet1t3zl9ERxcAwBTDMHT41ElTx3pcLt1dszTq7xgzGWxy6WgGEBF3v3hjq2aNmxDyNwN7GgIA0oHZvrV47mcdDwMHcJZOnaHNh/aFvZ+Z5xHNdklITUumXKVZ5RN7M5zT6Qh57VcuqNHeE8dScr9QIBEYQIStmV3t587JUUfXBW08uE8bD+6L6EPdTCmHtbVbVD22vLezgI1DEU+RDB76FRcUBpwVH4i3q0uPb3pFzmUOgg4AIKRAqwFD+cr1KzSldHRUj2W2nNYXFl8f1fmBUDq6ukytUPBvZQAAQKoy27dmp4pbgTKpx22u3Gi45xHNdklIXbPKJ/bLcuGqTEgyvcgEyAQMIMLW/HXOw3VidV261O9vMx/q/plM9c3vhR+A6e7Sy3t36dZZ89TQ2qJOVh8iTqJdzfp++zndOmte76z4c94OPfdWrbxdXUHv89z22n4D4QAA9BXpTOxhnnxVjSqN6DH6ziRvu9BpqpyWz+EIW7ob8HPl5Kh7wG+DYOy20gIAgEQw07cW637W8RQsk4bq7/Az8zyOtDSbnix31eixOnDyhKljYT/BXg/BqkxI0oPPPRXynPStIdPwSoet+eucRyvY5sl1TY168Lmn9KOXfq2X9u42da5NB/fJMAw6GmDK9DHjTB23dFp1VOd/8e2dqmtq7J0VX+TJDxum/XsBAAAwUDQzsSPd97Bv/npiy3o9/5a5PWfaO71atTD6PIjMYnbwULLXSgsAABLFTN9aLPtZx1OsqwPDPY+6pkY9tvkV0+dr+uD9qNsC64V6Pfj70+ZWTFJVSZmcTmdE+4UCmcL6bwYgDP/S8iJP/x/4+e7csPcN9KHun8lkdraRn7e7Ww2tLXQ0ICSHwyFJ2v/e8X5/DzTMk681y1bolurZg17bZvUdIE/VPQ0AAPZg5seyn/87LJLSPdHmL0k633VBs8ZX6NZZcyO+LxCMnVZaAACQaMH61qLJdYlkNpPmDyhnauZ5+PNoJFXFOkyseoT9OCTdu/SmiF/X9K0Bg1HCFCkh0NLyc94OPbl1Q9j79v1Qj3UmU3unV7PLJ5oqq4rM4srOUXfPJfl8/XfI9P99/dTpumJogYa6c1X0cYeVfxbUqgWLo9q82z9AXlVSlpJ7GgAA7MPsj+BbqmfrtqvnRTRDPdb8NfTjSWO3zpyjTQf36sLFi1GfC+khJytLl6LYQ7ovu6y0AAAgWYKVbbTT96HZTHrX/BoVefJNPw/2PUxdruwcff7a65XvztWmg3u19/ixsPepHjdBsydMjPix6FsDBrPPNwQQxsCl5UWefFP36/uhHsns+mDnirWsKtJTd0/ocll1x4/p+qkzNH9iVW9pBD//TECPyxXx4x4+dVI7G4/I8PlUFCbAMNMeABCM2R/BVWVjIu5kijV/9c18y6bOiPo8SH0el0v3r/iEFldNNXX89VOny2NyhYJhGKpvadbOxiOqb2kOuA0CAACpLlDZRjsxm0mLPPkRPY9Y8yisc8P0mZo1boKqSspUUjQsoY/l3y80FPrWkGlYgYiUFc0m0LEsMe97ruqx5bp11lz9vm5n1OdDZum7WjCQ6rHleibrtYjP+/KeXb3/Oy/MACQz7QEAwUSTq8yKR/6qa2rU2trN8kZQcgrpx3/93zraYOr46vEVunN+TdiVFnVNjXp2++v9Xv9FHo9WLVhsm5JuAABkgkRlUkpOpq7f1+1Ubf1BfXrhtfK43OHvIOmd5hMyDCPiPjD/opFQVcLoW0Om4dWOlBXNJtCxLDH3n6uuqVEPPvcUg4cZxMx+m2aECqwNrS1q6+yM6fz+Ov4DVzLabU8DAID9RJOrzIo1f+09cUyPblzH4CEkSfWnT8lrYj+ifHdu72BhqBUKwfbnPOf16tGN61TX1BjX9gMAgOASlUkpOZna2jo79ejGdTrbcd7U8d09PWpobYnqsVJlv1AgWViBiJTm/1AfOGN4mCdfKxfUDPpQNzOTyeFw9NvHru+5/B0MyBy3Xz1XN02/Wt99fm3M5S5CBdZ4zobLycrW/Stu0vmuC7bc0wAAYE+R5iqzYslf1WPL9Vc//4+oHhf2Nf7Kkfrk3IVq7/TqubdqTQ0I+jkG7DcdzPyKyrD5x8x+SM9tr1X12HKyFAAASZKITGomj8L+dpisQiHF1s+WCvuFAsnCACJSXiQf6maWon9l6Y3Kd+cOOhcbLmem2vp3dHP1nLCvmzyXq3cFYCDhSmzEczbcuU6vHE6n5lZMits5AQCZIRE/lmPJX4eb32PlYRr6oKNdVaNK5XQ6NSQ72/QEvWGefFWWjpb27g577IxxE8IeY2Y/pHBl6AEAQPzFO5OayaOwv46uLuUOGaILFy+GPTbWfjZ/FQsg0zFsjrQQySbQ4Zaizy6fGPBcbLicmfydRuFeN6trloY8T7gSG2Y2ava4XFpRfbWpdlPfHwAQrUhylVnR5q/606difmzYT0dXV29ZqWCvjUBWLqhR1ajSsMea3RvJbF4iVwEAkHzxzqSRZA7Y14KJk8MeE+3e7QAGYwUiMlI0M5noOMhc/msf7nUTS4kNM7Ph7q5ZqjyXW+v2vh22zdT3BwDYTTT5y2y5SqSevtm672tj3/Gj2t54pF9Z04F5KlxmMrs3ktm8RK4CACA9DMyjQ925evK1DWrr7LS6aTBp5vgJys5yav3+PUGPiXbvdgCDMYCIjBVsKbphGP06tipGFKvxTKuaz35oQSthB307jUKVMIi1xIaZOv+GYYSt289MKwCAXZkpBWQYho60NOtwS7Oa3j+dpJYh2QYOyvlfG1UlZbpj3qKQeSpeeyOZ2Q+JXAUAQHoZmEc/vfBaSpumCH8uqyop0/gRxfr5G1tDTjoDEDsGEIE+6poaB3VEOBwO+Zj9nrEi7TSKtUZ6uEFIMysVmWkFAEhVdU2NWlu7mX0P01y4fGUmT8VjbyRyFQAACDYxCcnjys7R8unV8smh39ftDHpc31w2u3yiZo2bENe92wEMxgAi8LG6psaAnQcMHtrf9VOn64qhBfqgvU1XFhSqMM+jJza/GvT4LIdDl01eVys6jcJ1msVr1j0AAHayq/GI/n3LequbgSSIV76KdeKWRK4CACDTDKw8Vllcouqx5drReER13qNWNy/jzC6v0JeX3NibDUdfMdx0LotHFgQQGgOISHmBvvglRTQDxTAMPbv99WQ1GXH2VmOD/u9n7+l3jbOdTj3z5mv96tjnDXFpStlovdvaEra+vd07jeIx6x4AgGgZhqH606fUcOqkfA6HqkaValJJWdTfQ7/cXquNB/fGuZWw2sBKHnbNV+QqAADST09Pj7YcPtA72fzaSVP16sG92nxwb79qFx6XS10XL5qeaI74Onyqud/f5DLAXhhAREryDxruO35UbzUeUUefetcel0s+SZ19wkCRx6NVCxYH7axoaG2hTEEK83Z36UhLsyaXjem9LVDg6Oi6oMc3vRL0PLfOmqtRhUX99r7c2XjEtmGFmVYAACvsPvqunq7dpK5Ll3pve1kfZbC7a5ZGPDj0b+t/r30nmuLbSCSEfwCwxzBCVntYNm2Gpo8Zr8uSGlua4zLInGjkKgAAUlOghQW/2vWmNhzY228i0/NvbQt4f0rnW8vb3aWX9+7SrbPm9d42MJcZhqH6lmYGFAELMIAI2xsYBDouXNAvd9QGHfAL9MV/zuvVoxvXac2yFQE7td4+9m7c243kqj99qt8AotQ/cBiGoQefeyrkOd448o4eWrlae08c03efX9vvNRZuEBoAgHQSqCPG6XTqhR3btH7/noD38XZ3h8xbA89/+NRJ/e7tHTp6pjUBzwDxMGPMeE0qLdNQd66K+uxbGC5TbX/3iHYde7dfxYc3yVIAACDOdh99V794c2u/hQVDsrN1safHwlYhUpsO7tPN1XMCDgrWNTUOKmlKHx2QPAwgwtYCfUnE4rnttaoeW97vC+n5t2q19Z0DcTk/rOPoM6ssUKenmVWmZ70dennvLr349uANm8MNQsdDsM5aAACSKeCP9DyPRhQUquH0qbD3f/bN1wflrYHn/+lrG9XdZwUj7OlcZ4ckafb4CmVnZ8swDG06tC9spvJ2dw26LZYsRUYCAAB9GYahJ7as1+4ACwIYPEw93u5uNbS2DKoGUdfUqEc3rht0fDL66AB8hAFE2FawL4lYnPV29PtCemHHNm04wH476aCydLSkjzs933xd5zr7d3rOLjcXKDYe3Bfy3wMNQscDM6oAAHYQ9Ed6p7ffd2so5zq9g8oQhTs/7OnEhx/oxIcf6IUdb2j6mHE68eGZmCf2RZqlyEgAAKCvuqZGPfX6Jl24eNHqpiCO2gf81jAMQ89ufz3kfRLVRwfgjxhAhC2Z+ZKI1o7GI5Kk8uEjtCFICS6kFld2tqpGlYbs9Aw3MOjXGab2/cBB6HhgRhUAwA7imb9efHunOi506bJ88l021NbVqUJ3rnYea4zL+ZFcPp8vbvtURpKlyEgAAKAvJqOlr4I8T7+/zVYSi3cfHYD+GECELZn5kojWtvpD2lZ/SFkOh3zhD0cKWD7jaknS2trNIY9zSCGvucflMrV59sBZUbFgRhUAwC7inb82v7M/budCetl3/GjYjh4yEgAA6Kunp0f/uW2L1c1ABBwOh7583Q16unazukOUlvW43L17bfud83aYegyzxwGIDr+0YEvxHKAJ5rKP4cN0kJOVrVuqZ+tIS3PYwb9wV3zptGpTjzlwVlQsIplRBQBAIiUjfwGS9FbjERmGEfIYMhIAAPCra2rUt579mTq6Bu+zDPvy+XzKd+cqKysr4vue77oQ1+MARIcBRNiOYRhqu9BpdTOQIi5d7tHuY42qP33K1PGzxleoyNN/AHCYJ19rlq3QiumzlO92h7z/ME/+oFlRsTDbWUunLgAgngzDUH1Ls3Y2HlF9S7MMw4jrBBlkpnx3rtzZOWGP6+jqCjvwR0YCAADSH8uWehk8TEmvHT4Qdrsgb3eXNh3a12+C2VB3rqnzmz0OQHQoYQpbqWtq1LPbX09Y+VKkpye2vKrxI4pNHeuQTz9Y+Xk1tLaovdOrgjyPKotLtPfEMX33+bVhZ7OtXFAT1zJZZjtr6dQFAMRLoLxV5PHorvk1KvJ4yGGIWkfXBQ3JNvcTM9zAHxkJAADEc49uWOPtpqOmjnv+rW3acGCPVi1Y/PHk/3xT9zN7HIDosAIRtuGfUUSnFaLRdKbV1HFvNx3V3hPHVFVSprkVk1RVUqa9J46Ffe35VynOGl8RryZLkiqLSwatiAz02PFc9QgAyFzB8tY5r1ePb3pFY4ePsKhlSBcXQ+xv01e4gT8yEgAAiPce3bC3c16vHt24TnVNjWRBwCYYQIQtMKMIyfSz1zbqYPN7MgzD1Gsv3+3W3975ubgPHkqS0+nUqgWLQx4T71WPAIDMZOY7b/97x5PUGmQyM509ZCQAAECp8sz03PZaSSILAjbAOwy2wIwiJFPXpUv6l3W/1Td//h96ee+usK+9jq4uNZpc4RiNWeMrtGbZiqB7MyZi4BIAkHmOtDSH/c7z+XxJag0ymdnOHjISAACZjVLlmemst0MNrS2aNb5Cy6fPlMPh6PfvDodDy6fPJAsCScAeiLCFfcfN1cMG4qmzu1svvr3T1LGJnvU2a3yFqseWD9qbkZlUAIB4qGtq1NO1m61uBjKMKztH3T2Xev8e5snXygU1EXX2kJEAAMgchmGo/vQpNZw6KZ/DIV2+bHWTYJH2Tq/qmhq1fv+eQf/m8/m0fv8eTRg5ikFEIMEYQITl6poatfHgPqubAYSUjFlvTqdTVSVlCX8cAEBm8e97CCRbdpZT//2GT+h814WYBv7ISAAApD//hLfO7m6rmwIbGOrO1U9f3xjymOe216p6bDkTy4AEYgARljIMQ8++yd6HsDc2ZQYApCqyFqzk7e6Ww+nU3IpJVjcFAICUYhhGRq2+Z8Ib+hrmyZfP4Qi7/YK/1CkTzYDEYQARlmpobdE5NkSGzbEpMwAgVb28dxdZC5ZKdBl4AADSTV1To57d/nq/wZMij0erFixOm3KNfQdI83Pz9Mwbr1ndJNjIygU16rjQaepYsiaQWAwgwlJ8yMMubrt6nmrrD/YL6NHs0wMAgF3UNTWa3usXSJRklIEHACBdBFuJd87r1aMb12nNshUp30cRaIAUkCSPy6Wl06p79782g6wJJBYDiLDUnuNHrW4CoKI8j26pnq1bqmdnVIkQAED6MgxDz26ndCmsRRl4AADMM5PfUn3PN0qVIhBXTo66L12St7tbv3t7h2rrD+qu+TUq8nhCDjSTNYHEYwARYSWq7vruY+9q97HGOLQQiM2qhYt7X9PUTQcA2EmkOcx/fH3ze8zqhuUoAw8AgHkNrS1ps+dboAwriQluCKj70qV+f5/zevX4ple0fPpMrd+/J+j9yJpA4jGAiJASVXfdMAw9/fqmeDQRiMm9S29K+fIfAID0FGkOoxwUrOJxueTt7u79mzLwAABEzuw2P3bfDihYhl1cNZWciojsOvqu7l16k365o5YthwCLMICIoBJZd/3lvbvUNWB2CWCF021/sLoJAAAMEmkOoxwUrOBwOPSVJTdq1vgJlIEHACBGZvdys/Oeb6EyLHtzI1JnvR3Kz83VD1Z+nqwJWIQBRASUyLrrhmFo48F9sTQPiJsX396p0mHDmbUEALCNSHMY+x3CKl9ZeqNml0+URBl4AABiVVlcktJ7vpFJEQlXdra6e3rCHtfe6ZXT6SRrAhZhqB4BRVJ3PRjDMFTf0qydjUdU39IswzAkSUdamtXZp8QRYLXnttf2vj4BALCa2Rx2pKVZ9S3N+t3bOygHhaQa5snXmmUregcPAQBA7JxOp1YtWBzyGDvv+WYmwwJ+y66aaeo4O6+4BTIBKxARUKx114PVO587oVLbjrwTlzYifTgcDvl8PsseP1U2IQcAZAazOeyxza8wKQtJt6Bysj5fs9S2nZcAAKSyWeMrtGbZikF9aqmw55vd92ZE9PLdbs2vmKQZ4yao/UKnntj8asznrCwpU1HDOym74hbIFAwgIqBY6q6Hqne+fv+eWJuGNOTz+XTn/EX6oL1NW945YEkbCLoAALswm8MYPIQVppWNYfAQAIAEmjW+QtVjy1NuzzezGfa2q+eptv4gqxVtzp2To1ULr9UV+UMHvf6ynU6trd0sbwy/RzoudGrVgsUh93G384pbIFMwgIiAzNRdz3fnqmJEsaSPy5WePqX6kye06dD+ZDUTNpGdlaUZY8bp7aajUZ+jMDdPY4aPiMsA4p3zF6kwN08FeR4daWnW7+vCb9RNSQQAgF2YyWGAVchMAAAkXiru+WYmw7pzcjT+ypEqHzlKjS3NOnn2D9p34lgSWwmzui5d0hX5QwO+DmeNr5B7iEv/9PJvoj5/QZ5HVSVlKbviFsgUDCAiIH/d9VCzQDq6Lui7z6/tLUvKLPjM1XP5ssquGB7TAOJQd25cOkyHefJ1/dQZvTOUKotLVFt/UG2dnSHvQ0kEAIBdmMlhyGwel0v3Lr1JlyX9y7rfxu2c4WaRk5kAAEAwZjJs16VL+tdXf5fEViEWoap1VY0qjboPrzA3rzdTpuqKWyBT8E5EUP6660We4LOM/WVJGTzE64cPqSiGGelPvrZBe08cC7theDgDyxs4nU59euG1Ed0HAACr+XOYx+Wyuimwobtrlmpy2RhNKSmLy2tkmCdfn71mSdjjyEwAACAUM32JSB2hKk/4B4yj8elrrh3Ud1dVUqa5FZNUVVJG3gRshHcjQpo1vkLf+5PPyp2TY3VTYHPnOr2qmTwt6vu3dXb2zlILFDZdYV6DHpdba5atCFjeIFiAHebJD3ofAACsNq10jHouX7a6GbCRgdll74ljMe0947dyQY1mT5ioNctWKC/AgGSonAUAAOBnGIbyXG59cvYC+hJTnJnKE8H621zZga+9KzuHTAmkGEqYIqS6pkat3bZFXZcuWd0UpIDigsKAtcv9HA6HfD5fyHM8t71WD61cHbB8Qd3xo/r5G1vl7erqPd7jcun6aTN0c/WckDOUKIkAALCznp4ebX7ngN5tadaFnks69YcP1dHdFf6OSHvunBwtmjRFM8ZN6JddDMPQs9tfN30eV3a2spxOdV682HvbwP1l/Hmp/vQpNZw6KZ/DoapRpZrETHAAABBGXVNj0P4gpB6zlSeC9bcZhqHNh/br3fdb5M7O0bzKyZpCpgRSDgOICGr30Xf1+OZXrG4GbMDjcstrohPTvwGyPzic83bofNcFDXXnqsiTrx7DCLtPz1lvhxpaW1RVUjZoo+bZ5RM1a9yEqAcBU3ETcgBAejMMQ09sWa/dx961uimwoTvmLdKyaTMCZp2Pslb4DrqbZ87R5NLRvTPIw+Uop9OpKaWjNaV0dHyeBAAASHt1TY3s351C/Pmwo+uCfvlWbb9MOXCCmRmB+tucTqeWz5il5ZoVt3YDSD4GEDOYYRhBOxB2H3tX/77lVYtbCKt5XC7du/QmTSwu0XefXxuyk6pvaYNgA3U7G4+YetxQmzQzCAgASAeGYeilvbu1bs8u9RiG1c2BDRXleYIOHkqh81JfpUXD+mUnchQAADArVN9h32PW1m62qIWIlMfl0u2z5vZex1gm6gNIfwwgZqi6pkY9++brOten4yFviEvjR4yUt6tLxz88Y2HrYBd31yzV5LIxkqRVCxaHnE1mprRBqM2XozkOAAA7G9jhUjGiWI1nWrXv+FHV1r+j7h5KxKcrh6Qsp7Pf4LDH5dLCysnadexdUysHVy1cHDJbkasAAEAiBSpJWuTx6K55Ncpzu1V/6j39oeO8Tv7hw7jsyYzkWDqtul/GZKI+gFAYQMxAwcoKdF7s1qHm9yxoEewmULkC/8bIA8NjJKUNKotLVOTxmF7JCABAqgrU4WJmL2CkB5+ke5YsV747d9Bs7j+Ze40aWlu07/hRbTvyzqC9xj0ut+6uWRI2W5GrAABAogTrOzzn9bLdUQrzuNy6pXq21c0AkEIYQMwwlBXAQPlut35w12od+/BM2HIFwTZGjmQPwnisZAQAwM6CdbgweJhZnn9rmx5auTrgHoP+vZ7vmLdIR1qaVX/6lBw+nypLR6tqVKmpLESuAgAAiWAYhp7d/rrVzUAC3F2zhGwIICIMIGaYIy3NlBVAP59btERDhgwxXa4g1tIG8VjJCACAXdHhAr+z3g41tLaEzE1Op1OTy8b0loyPFLkKAADEW0Nri6ly67CvfLdbHV1dvX+TDQFEiwHEDFN/+pTVTYBF7BQeYl3JCACAXdHhgr7aOxP/WiBXAQCAeEpGfkFi3TW/RkWefLIhgJgxgJhhHJTOykjDPPn62zs/p8YzrbYJD2zSDABIR3S4oK+CPE9SHodcBQAA4iVZ+QWJU+TJJxsCiAsGEDNMZeloae9uq5uBJFu5oEbZ2dmEBwAAEowOl/TkkOQeMkQXLl78420OR8h9LYd58lVZXJKE1gEAAMRPZXGJijweqmpYxONyy9vdFf7AIMigAOKJAcQM0tPToyZKmKa8W2fOVdelbm08uC/ssdQ4BwAguehwST+u7Bz9f5/7kpxOZ78yoR1dF/T4pleC3m/lghpKRQEAgJTjdDq1asFiPbpxndVNySh5Q1z60+tv0qSSMu09cSzgHtdzJkzUG0fekbe7O+h5yKAA4okBxDRnGIYaWlu0YX+d9r933OrmIEb3Xn+TZpdPlCRNHFWqZ958TW2dnb3/Xpibp2unTNPIgiJblCkFACDTOJ1OzZ1QqfX791jdFMTJF69bpuzsj342Dazm4FzmCNi5wwQuAAAARGL14qWaXDZGUug9rv/bnIV6ee8ubTy4T519BhLJoAASgQHENFbX1Khn33xd59iLJ+V5XG7dXbOkXwgIFSYAAIA1enp69GbDYaubgTgw0wlDHgMAAOnGMAw9u/11q5uRMQL1+UnB97h2Op26ddY83Vw9hwwKIOEYQExTdU2NlBpIAx6XS9dPm6Gbq+cEDAHBwgQAAEi+uqZG/XTrRnX3XLK6KYiSKztHNVVTNGPcBNOdMOSx5PFXV6GjDACAxGlobaEcfxIMycrWTdWzgvb5hUMGRTTI04gUA4hpyDAM/fS1jVY3A1FaMLFKU8rGqOjjTY/5EAcAwP6YvJX67pi3SMumzSB72VRdU+OgcrFFHo9WLVhMqS4AAOKonUpmSfGFa5dp9oSJVjcDGYQ8jWjw6zgNHT51Ut2XmPmeim6dNVdfvO4GzZ9YpaqSMjqwAABIAYZh6MmtG6xuBmIwzJPP4KGN+QfoB66GOOf16tGN61TX1GhRywAASD9D3blWNyEjPL9jmwzDsLoZyBDkaUSLFYhp6Pd1O61uAqKQN8SlW2fOsboZAAAgjJ6eHm05fEAftLdp+NACnfjgjC729FjdLMRg5YIaBg9tysw+TM9tr1X12HKuIQAAUfCXNDzn7dD5rgs6T/nSpDjr7VBDawtlSJFw5GnEggHEFNPT06PN7xxQ4+lTysnJ0eiiK3Sh56LkkzzuXL3VcFgnz35odTMRhdWLl/IhDQCAhfruB+FxuXXyDx+o8XSLui/3aNzwkZo8eowOHD+mjYf2Wd1URMmdk6OuPpU6hnnytXJBDSV7bMzMPkx0wAEAEF7frDvUnSufw6F9x49p+7uHdeHiRaubl5EoF4tkIE8jFgwgppAXdmzThv175OtzG2sNU0/ukCH9gllRnkerFlJrGgAAKwXaD6Kvw6dO6pX9bye5VYi3z1xznYo8+Wrv9Kogz8N+0ynAbMcaHXAAAAQXLuvCGgV5HqubgAxAnkYsGEBMES/s2Kb1+/dY3QzEwZrrV8jhdNJxBQCATfj3g0D6K/LkM6s2xZjtWKMDDgCAwMi69jTMk6/K4hKrm4EMQJ5GLBhATAE9PT3acGCv1c1AHAzz5GtSSRkDhgAA2ISZ/SCQHuikSU2VxSUq8nhCrpjg2gIAEBhZ177YgxvJQp5GLPiUSgFbDh+Qz+cLfyBsj3AAAIC9mNkPAumBHJaanE6nVi1YHPIYri0AAIGRde1nmCdfa5atYCsjJA15GrFgBWIK+KC9zeomoA9Xdo6ys5zydnf33laU59HiyVN15dBCHT71nvYcP9Zvn8NhnnytXFBDOAAAwGbY5yG15bvdmjehUlcMLdBQd64+ON+m1w4fVFtnZ+8x5LDUN2t8hdYsWzFo7yauLQAAoZF1Eyff7db8iknKc7kG5c++/H2GIwuK2MoIliFPI1oMIKaAKwsKrW5Cxst2OjV9zDhdN2W6Jn28b05Da0vAfQznT6zSasMI+u8AAMA+2OfBfrKdTs0ur1CRZ6j+4D0v+aThQ4eqqnSMKkeOUuOZ1pAZ6+bqOeSwNDRrfIWqx5ZzbQEAiABZNz5ml1fonmtvCJpD++bP/Nw8OXw+ne+6QF6BrZCnEQ0GEFPAkslX6YUdb1DGNIGckqaPHa+JxaUqyMtTQZ4n7Jd91ccDiQHP53SG/HcAAGAPZvaDQOK5c3K0aNIUzRg3IeyP2HAZixyWvri2AABEhqwbGYekvr2v+W63PnPNdZpdPlFS8BxKRkGq4LWKSDGAmAKys7N1w1XVWr9/j9VNSRtXeobqumnTVZCbp6KPN4lltgUAAJnHvx/EoxvXWd2UjOJxuVRVUqbioitUNapUk0rKyGIAAABxRtYNLycrS//9hls0uXS0pOAVxwAgEzGAmCLumLdIkrRh/x6xDtGcIVlZunpCpVbOWahf79mpM23nNKKwSHfOWaghQ4ZY3TwAAGATwfaDQHSKC4o0dvgIyenQlZ58TSozV3oUAAAA8UfWDe1LS5Zr6uixvX+zOgsA/sjhoy5mwrS3t6uwsFBtbW0qKCiIyzl7enq0+Z0Dajx9Sjk5ORpddIWOffC+3mk+oe6ent7jshxOFRcW6nTbORlJvsQOfTTD6bJh9N6W48zSJeNyQh832+HUiplXq7hwGB1TAIC4SsR3OqKXqOth9NnD2ONy6+QfPlDj6RZ90NGuM+1tunj5j1kmy+HQlUMLNGlUmbKys7Tl0P64tSMVZTmcmjexUp+7Zomys5mjCAAwj5xlL1yP9NU3655uO6fNh/aps7vb1H3zcoZowqgSHXjveIJbmTzDPPlauaBGs8ZXWN0UAEiYWL/X+XWfYrKzs7V8+kwtnz6z3+19Q0DfwTPDMFR/+pQaTp1U89kPdeDkiX4De5HId7s1v2KSpo8Zr4bTzdpwcJ+6L13q/XdXTo5uuGqmbp05R9LgJf97TxwbNNvJ6XBIPp/6tijb6VTpsCuUN8Sl/Nw8ne1o1/EPzqinT7td2dmaOW6CrvDkS04npa8AAEDMBu4HMXX0WGnGR/87WNbyqyop0y/e2Kr2Cxd6byvMzdOcCRO17cg76uqTmbKdTg3NzVXHhQu6FCSXTRs9VuOvHKGNB/f1u++QrCyNLCjShx3tutDndo/LpSVTZ2jiqFK1d3p1vuuChrpzVeTJV0fXBf3yrdp+GSzH6ZTP51NPn4lmTodDZcOuUFdPjz44395v/+2crCxdNXqsrpsyXROLS9Tw/mk1nDopn8NBDgMAAEgBA7PurTPn9Obb99vP6bXDB9XW2dn77/5+wL57VNc1NUa9kjHHmaWqstE6dqZV3q6u3tuznE5VFo/SyKIrVD58hDq6u+W92C2nJDkc2vLO/n4DnTlZWRpZUKhhnnxd7LmkC90XleV0qqvnkjovXlRnd1e/PkS/ojyPFk+eqpEFRSw8AACTWIGYQHactTWw86tiRLHebW3RO6dO6vgH78uVla2JJWVaOuUqOZ3OkB1l4TrSzDx+ZXGJpPD1xaN5LAAA4sWO3+mZzK7XI9SErlC3/6HjvI6daZVD0oiCQi2ZfFXvKr5IzxlJ26TgGYzsBQBIFrt+r2cqrkfmMpv/wuXK/Nw8+QxDR1qa9Qdvh4Z/XNK+alRp3HKsmePPeTv6TaojzwLIRLF+rzOAmECELgAA0gPf6fbC9QAAIH3wvW4vXA8AANJHrN/rTLsAAAAAAAAAAAAA0IsBRAAAAAAAAAAAAAC9GEAEAAAAAAAAAAAA0IsBRAAAAAAAAAAAAAC9GEAM49/+7d9UXl4ut9ut2bNn6/XXX7e6SQAAAGmBnAUAABB/ZCwAABAPDCCG8Oyzz+r+++/Xd77zHdXV1Wnx4sW6+eabdeLECaubBgAAkNLIWQAAAPFHxgIAAPHi8Pl8PqsbYVfz58/X1VdfrUceeaT3tilTpuhTn/qUHn744bD3b29vV2Fhodra2lRQUJDIpgIAgATiOz3+YslZXA8AANIH3+vxRV8WAADwi/V7nRWIQVy8eFG7d+/WjTfe2O/2G2+8UW+88UbA+3R3d6u9vb3ffwAAAOgv0pxFxgIAAAiPviwAABBPDCAG8cEHH+jy5csqLi7ud3txcbFOnz4d8D4PP/ywCgsLe/8bM2ZMMpoKAACQUiLNWWQsAACA8OjLAgAA8cQAYhgOh6Pf3z6fb9Btft/+9rfV1tbW+997772XjCYCAACkJLM5i4wFAABgHn1ZAAAgHrKtboBdXXnllcrKyho0Q+v9998fNJPLz+VyyeVyJaN5AAAAKSvSnEXGAgAACI++LAAAEE+sQAxiyJAhmj17ttavX9/v9vXr1+uaa66xqFUAAACpj5wFAAAQf2QsAAAQT6xADOGBBx7Q6tWrNWfOHC1cuFCPPfaYTpw4oT/7sz+zumkAAAApjZwFAAAQf2QsAAAQLwwghrBq1Sp9+OGH+t73vqeWlhZdddVVeumllzRu3DirmwYAAJDSyFkAAADxR8YCAADx4vD5fD6rG5Gu2tvbVVhYqLa2NhUUFFjdHAAAECW+0+2F6wEAQPrge91euB4AAKSPWL/X2QMRAAAAAAAAAAAAQC8GEAEAAAAAAAAAAAD0YgARAAAAAAAAAAAAQC8GEAE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      "text/plain": [
       "<Figure size 2200x1700 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = ['Weight', 'Depth','Table', 'X_length', 'Y_width', 'Z_Depth']\n",
    "plt.figure(figsize=(22, 17))\n",
    "for i in range(6) :\n",
    "    plt.subplot(2,3,i+1)\n",
    "    #sns.set()\n",
    "    plt.scatter(df[cols[i]],df['Price'],color='#679C94')\n",
    "    plt.title(cols[i])\n",
    "    plt.ylabel('Price',size=13)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8fdca69-72d9-4d59-8d2a-4c0bb97c5ed1",
   "metadata": {},
   "source": [
    "#### -> we can see the relation between all factors of the diamond and the price "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cccded9a-2eba-4c21-ac26-03b9f58b74a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cut_Quality</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fair</td>\n",
       "      <td>3701.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Premium</td>\n",
       "      <td>3485.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Very Good</td>\n",
       "      <td>3222.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Good</td>\n",
       "      <td>3215.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ideal</td>\n",
       "      <td>2801.71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Cut_Quality    Price\n",
       "0        Fair  3701.98\n",
       "1     Premium  3485.01\n",
       "2   Very Good  3222.78\n",
       "3        Good  3215.51\n",
       "4       Ideal  2801.71"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quality = df.groupby('Cut_Quality').mean().sort_values('Price',ascending=False)\n",
    "quality = quality[['Price']].round(2)\n",
    "quality.reset_index(inplace=True)\n",
    "quality "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bccbe692-a30e-474a-924c-144db76d968b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x= quality['Cut_Quality'],y=quality['Price'], palette='bone')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "707f0a7b-367f-4c14-826d-abb87779810d",
   "metadata": {},
   "source": [
    "#### -> we see the average price for every cut quality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8d750658-784a-4433-a5d0-5efdb4dc80b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Color</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>J</td>\n",
       "      <td>3895.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>I</td>\n",
       "      <td>3627.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>H</td>\n",
       "      <td>3507.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>G</td>\n",
       "      <td>3209.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>F</td>\n",
       "      <td>3069.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>D</td>\n",
       "      <td>2654.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>E</td>\n",
       "      <td>2588.76</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Color    Price\n",
       "0     J  3895.46\n",
       "1     I  3627.18\n",
       "2     H  3507.42\n",
       "3     G  3209.37\n",
       "4     F  3069.83\n",
       "5     D  2654.11\n",
       "6     E  2588.76"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color = df.groupby('Color').mean().sort_values('Price',ascending=False)\n",
    "color = color[['Price']].round(2)\n",
    "color.reset_index(inplace=True)\n",
    "color "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "114b1ec4-ec44-44d3-bd73-8f42a1719184",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VWFiYpk2bpsbGRo0bN05r1qxRt27d7Jp169ZpwYIF9tNomZmZKioq6tzJAgCAkBXUQLRq1aqL7nc4HMrLy1NeXl67NT169FBhYaEKCwvbrYmOjlZxcXFH2wQAADe4kLuHCAAAoLMRiAAAgPEIRAAAwHgEIgAAYDwCEQAAMB6BCAAAGI9ABAAAjEcgAgAAxiMQAQAA4xGIAACA8QhEAADAeAQiAABgPAIRAAAwHoEIAAAYj0AEAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAAGA8AhEAADAegQgAABiPQAQAAIxHIAIAAMYLC3YDAABcC+/+8Y/BbuG6mzJyZLBbuGGxQgQAAIxHIAIAAMYjEAEAAOMRiAAAgPEIRAAAwHg8ZQYAwA3ui6qqYLdw3X0nMfGq3s8KEQAAMB6BCAAAGI9ABAAAjBfUQFRQUKB7771XkZGRio2N1cMPP6yDBw8G1MycOVMOhyNgGz58eECN3+/X/PnzFRMTo4iICGVmZur48eMBNbW1tcrOzpbL5ZLL5VJ2drbq6uqu9xQBAEAXENRAtHXrVs2bN0/l5eUqLS3V2bNnNXHiRJ05cyagLj09XdXV1fb24YcfBuzPycnRhg0bVFJSorKyMjU0NCgjI0MtLS12TVZWliorK+XxeOTxeFRZWans7OxOmScAAAhtQX3KzOPxBLxevXq1YmNjVVFRoQceeMAedzqdcrvdbR7D5/Np1apVWrt2rcaPHy9JKi4uVmJiojZt2qRJkybpwIED8ng8Ki8vV2pqqiRp5cqVSktL08GDBzVgwIDrNEMAANAVhNQ9RD6fT5IUHR0dML5lyxbFxsaqf//+mj17tmpqaux9FRUVam5u1sSJE+2xhIQEJScna9u2bZKk7du3y+Vy2WFIkoYPHy6Xy2XXXMjv96u+vj5gAwAAN6aQCUSWZWnhwoW6//77lZycbI9PnjxZ69at0+bNm/Xqq69q165dGjt2rPx+vyTJ6/UqPDxcvXr1CjheXFycvF6vXRMbG9vqM2NjY+2aCxUUFNj3G7lcLiVe5fcbAACA0BUyX8z41FNPac+ePSorKwsYnz59uv1zcnKyhg0bpr59++qDDz7QlClT2j2eZVlyOBz262//3F7Nty1evFgLFy60X9fX1xOKAAC4QYXECtH8+fP1/vvv6+OPP1afPn0uWhsfH6++ffvq0KFDkiS3262mpibV1tYG1NXU1CguLs6uOXHiRKtjnTx50q65kNPpVFRUVMAGAABuTEENRJZl6amnntK7776rzZs3q1+/fpd8z6lTp1RVVaX4+HhJUkpKirp3767S0lK7prq6Wvv27dOIESMkSWlpafL5fNq5c6dds2PHDvl8PrsGAACYK6iXzObNm6f169frd7/7nSIjI+37eVwul3r27KmGhgbl5eVp6tSpio+P19GjR/Xss88qJiZGjzzyiF07a9Ys5ebmqnfv3oqOjtaiRYs0ePBg+6mzgQMHKj09XbNnz9aKFSskSXPmzFFGRgZPmAEAgOAGouXLl0uSRo8eHTC+evVqzZw5U926ddPevXv11ltvqa6uTvHx8RozZozefvttRUZG2vVLly5VWFiYpk2bpsbGRo0bN05r1qxRt27d7Jp169ZpwYIF9tNomZmZKioquv6TBAAAIS+ogciyrIvu79mzpz766KNLHqdHjx4qLCxUYWFhuzXR0dEqLi6+4h4BAMCNLyRuqgYAAAgmAhEAADAegQgAABiPQAQAAIxHIAIAAMYjEAEAAOMRiAAAgPEIRAAAwHgEIgAAYDwCEQAAMB6BCAAAGI9ABAAAjEcgAgAAxiMQAQAA4xGIAACA8QhEAADAeAQiAABgPAIRAAAwHoEIAAAYj0AEAACMRyACAADGu6pAdPjwYX300UdqbGyUJFmWdU2aAgAA6EwdCkSnTp3S+PHj1b9/f/3DP/yDqqurJUmPP/64cnNzr2mDAAAA11uHAtGPf/xjhYWF6dixY7r55pvt8enTp8vj8Vyz5gAAADpDWEfetHHjRn300Ufq06dPwHhSUpK+/PLLa9IYAABAZ+nQCtGZM2cCVobO++tf/yqn03nVTQEAAHSmDgWiBx54QG+99Zb92uFw6Ny5c/rFL36hMWPGXLPmAAAAOkOHLpn94he/0OjRo7V79241NTXpmWee0f79+/X111/rj3/847XuEQAA4Lrq0ArRoEGDtGfPHt13332aMGGCzpw5oylTpuizzz7TnXfeea17BAAAuK46tEIkSW63Wz/72c+uZS8AAABB0aEVotWrV+udd95pNf7OO+/ozTffvOqmAAAAOlOHAtHLL7+smJiYVuOxsbHKz8+/6qYAAAA6U4cC0Zdffql+/fq1Gu/bt6+OHTt21U0BAAB0pg4FotjYWO3Zs6fV+J/+9Cf17t37qpsCAADoTB0KRI8++qgWLFigjz/+WC0tLWppadHmzZv19NNP69FHH73s4xQUFOjee+9VZGSkYmNj9fDDD+vgwYMBNZZlKS8vTwkJCerZs6dGjx6t/fv3B9T4/X7Nnz9fMTExioiIUGZmpo4fPx5QU1tbq+zsbLlcLrlcLmVnZ6uurq4j0wcAADeYDgWin//850pNTdW4cePUs2dP9ezZUxMnTtTYsWOv6B6irVu3at68eSovL1dpaanOnj2riRMn6syZM3bNK6+8oiVLlqioqEi7du2S2+3WhAkTdPr0absmJydHGzZsUElJicrKytTQ0KCMjAy1tLTYNVlZWaqsrJTH45HH41FlZaWys7M7Mn0AAHCD6dBj9+Hh4Xr77bf14osv6k9/+pN69uypwYMHq2/fvld0nAv/EOzq1asVGxuriooKPfDAA7IsS8uWLdNzzz2nKVOmSJLefPNNxcXFaf369XriiSfk8/m0atUqrV27VuPHj5ckFRcXKzExUZs2bdKkSZN04MABeTwelZeXKzU1VZK0cuVKpaWl6eDBgxowYEBHTgMAALhBdGiF6Lz+/fvr+9//vjIyMq44DLXF5/NJkqKjoyVJR44ckdfr1cSJE+0ap9OpUaNGadu2bZKkiooKNTc3B9QkJCQoOTnZrtm+fbtcLpcdhiRp+PDhcrlcds2F/H6/6uvrAzYAAHBjuuwVooULF+rFF19URESEFi5ceNHaJUuWXHEjlmVp4cKFuv/++5WcnCxJ8nq9kqS4uLiA2ri4OH355Zd2TXh4uHr16tWq5vz7vV6vYmNjW31mbGysXXOhgoICvngSAABDXHYg+uyzz9Tc3CxJ+vTTT+VwONqsa2/8Up566int2bNHZWVllzymZVmX/JwLa9qqv9hxFi9eHBD86uvrlZiYeNHPBAAAXdNlB6KPP/7Y/nnLli3XtIn58+fr/fff1yeffKI+ffrY4263W9L/rfDEx8fb4zU1NfaqkdvtVlNTk2prawNWiWpqajRixAi75sSJE60+9+TJk61Wn85zOp1yOp1XPzkAABDyrvgeorNnzyosLEz79u276g+3LEtPPfWU3n33XW3evLnVlz3269dPbrdbpaWl9lhTU5O2bt1qh52UlBR17949oKa6ulr79u2za9LS0uTz+bRz5067ZseOHfL5fHYNAAAw1xU/ZRYWFqa+ffsGPNLeUfPmzdP69ev1u9/9TpGRkfb9PC6XSz179pTD4VBOTo7y8/OVlJSkpKQk5efn6+abb1ZWVpZdO2vWLOXm5qp3796Kjo7WokWLNHjwYPups4EDByo9PV2zZ8/WihUrJElz5sxRRkYGT5gBAICOPXb/r//6r1q8eLGKi4vtJ8I6Yvny5ZKk0aNHB4yvXr1aM2fOlCQ988wzamxs1Ny5c1VbW6vU1FRt3LhRkZGRdv3SpUsVFhamadOmqbGxUePGjdOaNWvUrVs3u2bdunVasGCB/TRaZmamioqKOtw7AAC4cXQoEL3++us6fPiwEhIS1LdvX0VERATs//TTTy/rOJZlXbLG4XAoLy9PeXl57db06NFDhYWFKiwsbLcmOjpaxcXFl9UXAAAwS4cC0cMPPyyHw3FZgQYAACDUXVEg+tvf/qaf/OQneu+999Tc3Kxx48apsLBQMTEx16s/AACA6+6KnjJ7/vnntWbNGn3ve9/TD37wA23atEk/+tGPrldvAAAAneKKVojeffddrVq1yv6L9o899phGjhyplpaWgBuYAQAAupIrWiGqqqrSd7/7Xfv1fffdp7CwMH311VfXvDEAAIDOckWBqKWlReHh4QFjYWFhOnv27DVtCgAAoDNd0SUzy7I0c+bMgD9p8c033+jJJ58MePT+3XffvXYdAgAAXGdXFIhmzJjRauyHP/zhNWsGAAAgGK4oEK1evfp69QEAABA0V/zHXQEAAG40BCIAAGA8AhEAADAegQgAABiPQAQAAIxHIAIAAMYjEAEAAOMRiAAAgPEIRAAAwHgEIgAAYDwCEQAAMB6BCAAAGI9ABAAAjEcgAgAAxiMQAQAA4xGIAACA8QhEAADAeAQiAABgPAIRAAAwHoEIAAAYj0AEAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAAGC8oAaiTz75RA8++KASEhLkcDj03nvvBeyfOXOmHA5HwDZ8+PCAGr/fr/nz5ysmJkYRERHKzMzU8ePHA2pqa2uVnZ0tl8sll8ul7Oxs1dXVXefZAQCAriKogejMmTMaOnSoioqK2q1JT09XdXW1vX344YcB+3NycrRhwwaVlJSorKxMDQ0NysjIUEtLi12TlZWlyspKeTweeTweVVZWKjs7+7rNCwAAdC1hwfzwyZMna/LkyRetcTqdcrvdbe7z+XxatWqV1q5dq/Hjx0uSiouLlZiYqE2bNmnSpEk6cOCAPB6PysvLlZqaKklauXKl0tLSdPDgQQ0YMKDNY/v9fvn9fvt1fX19R6YIAAC6gJC/h2jLli2KjY1V//79NXv2bNXU1Nj7Kioq1NzcrIkTJ9pjCQkJSk5O1rZt2yRJ27dvl8vlssOQJA0fPlwul8uuaUtBQYF9ic3lcikxMfE6zA4AAISCkA5EkydP1rp167R582a9+uqr2rVrl8aOHWuv3Hi9XoWHh6tXr14B74uLi5PX67VrYmNjWx07NjbWrmnL4sWL5fP57K2qquoazgwAAISSoF4yu5Tp06fbPycnJ2vYsGHq27evPvjgA02ZMqXd91mWJYfDYb/+9s/t1VzI6XTK6XR2sHMAANCVhPQK0YXi4+PVt29fHTp0SJLkdrvV1NSk2tragLqamhrFxcXZNSdOnGh1rJMnT9o1AADAbF0qEJ06dUpVVVWKj4+XJKWkpKh79+4qLS21a6qrq7Vv3z6NGDFCkpSWliafz6edO3faNTt27JDP57NrAACA2YJ6yayhoUGHDx+2Xx85ckSVlZWKjo5WdHS08vLyNHXqVMXHx+vo0aN69tlnFRMTo0ceeUSS5HK5NGvWLOXm5qp3796Kjo7WokWLNHjwYPups4EDByo9PV2zZ8/WihUrJElz5sxRRkZGu0+YAQAAswQ1EO3evVtjxoyxXy9cuFCSNGPGDC1fvlx79+7VW2+9pbq6OsXHx2vMmDF6++23FRkZab9n6dKlCgsL07Rp09TY2Khx48ZpzZo16tatm12zbt06LViwwH4aLTMz86LffQQAAMwS1EA0evRoWZbV7v6PPvroksfo0aOHCgsLVVhY2G5NdHS0iouLO9QjAAC48XWpe4gAAACuBwIRAAAwHoEIAAAYj0AEAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAAGA8AhEAADAegQgAABiPQAQAAIxHIAIAAMYjEAEAAOMRiAAAgPEIRAAAwHgEIgAAYDwCEQAAMB6BCAAAGI9ABAAAjEcgAgAAxiMQAQAA4xGIAACA8QhEAADAeAQiAABgPAIRAAAwHoEIAAAYj0AEAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAAGA8AhEAADBeUAPRJ598ogcffFAJCQlyOBx67733AvZblqW8vDwlJCSoZ8+eGj16tPbv3x9Q4/f7NX/+fMXExCgiIkKZmZk6fvx4QE1tba2ys7PlcrnkcrmUnZ2turq66zw7AADQVQQ1EJ05c0ZDhw5VUVFRm/tfeeUVLVmyREVFRdq1a5fcbrcmTJig06dP2zU5OTnasGGDSkpKVFZWpoaGBmVkZKilpcWuycrKUmVlpTwejzwejyorK5WdnX3d5wcAALqGsGB++OTJkzV58uQ291mWpWXLlum5557TlClTJElvvvmm4uLitH79ej3xxBPy+XxatWqV1q5dq/Hjx0uSiouLlZiYqE2bNmnSpEk6cOCAPB6PysvLlZqaKklauXKl0tLSdPDgQQ0YMKDNz/f7/fL7/fbr+vr6azl1AAAQQkL2HqIjR47I6/Vq4sSJ9pjT6dSoUaO0bds2SVJFRYWam5sDahISEpScnGzXbN++XS6Xyw5DkjR8+HC5XC67pi0FBQX2JTaXy6XExMRrPUUAABAiQjYQeb1eSVJcXFzAeFxcnL3P6/UqPDxcvXr1umhNbGxsq+PHxsbaNW1ZvHixfD6fvVVVVV3VfAAAQOgK6iWzy+FwOAJeW5bVauxCF9a0VX+p4zidTjmdzivsFgAAdEUhu0LkdrslqdUqTk1Njb1q5Ha71dTUpNra2ovWnDhxotXxT5482Wr1CQAAmClkA1G/fv3kdrtVWlpqjzU1NWnr1q0aMWKEJCklJUXdu3cPqKmurta+ffvsmrS0NPl8Pu3cudOu2bFjh3w+n10DAADMFtRLZg0NDTp8+LD9+siRI6qsrFR0dLRuv/125eTkKD8/X0lJSUpKSlJ+fr5uvvlmZWVlSZJcLpdmzZql3Nxc9e7dW9HR0Vq0aJEGDx5sP3U2cOBApaena/bs2VqxYoUkac6cOcrIyGj3CTMAAGCWoAai3bt3a8yYMfbrhQsXSpJmzJihNWvW6JlnnlFjY6Pmzp2r2tpapaamauPGjYqMjLTfs3TpUoWFhWnatGlqbGzUuHHjtGbNGnXr1s2uWbdunRYsWGA/jZaZmdnudx8BAADzBDUQjR49WpZltbvf4XAoLy9PeXl57db06NFDhYWFKiwsbLcmOjpaxcXFV9MqAAC4gYXsPUQAAACdhUAEAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAAGA8AhEAADAegQgAABiPQAQAAIxHIAIAAMYjEAEAAOMRiAAAgPEIRAAAwHgEIgAAYDwCEQAAMB6BCAAAGI9ABAAAjEcgAgAAxiMQAQAA4xGIAACA8QhEAADAeAQiAABgPAIRAAAwHoEIAAAYj0AEAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAAGA8AhEAADAegQgAABiPQAQAAIwX0oEoLy9PDocjYHO73fZ+y7KUl5enhIQE9ezZU6NHj9b+/fsDjuH3+zV//nzFxMQoIiJCmZmZOn78eGdPBQAAhLCQDkSSdPfdd6u6utre9u7da+975ZVXtGTJEhUVFWnXrl1yu92aMGGCTp8+bdfk5ORow4YNKikpUVlZmRoaGpSRkaGWlpZgTAcAAISgsGA3cClhYWEBq0LnWZalZcuW6bnnntOUKVMkSW+++abi4uK0fv16PfHEE/L5fFq1apXWrl2r8ePHS5KKi4uVmJioTZs2adKkSZ06FwAAEJpCfoXo0KFDSkhIUL9+/fToo4/qz3/+syTpyJEj8nq9mjhxol3rdDo1atQobdu2TZJUUVGh5ubmgJqEhAQlJyfbNe3x+/2qr68P2AAAwI0ppANRamqq3nrrLX300UdauXKlvF6vRowYoVOnTsnr9UqS4uLiAt4TFxdn7/N6vQoPD1evXr3arWlPQUGBXC6XvSUmJl7DmQEAgFAS0oFo8uTJmjp1qgYPHqzx48frgw8+kPR/l8bOczgcAe+xLKvV2IUup2bx4sXy+Xz2VlVV1cFZAACAUBfSgehCERERGjx4sA4dOmTfV3ThSk9NTY29auR2u9XU1KTa2tp2a9rjdDoVFRUVsAEAgBtTlwpEfr9fBw4cUHx8vPr16ye3263S0lJ7f1NTk7Zu3aoRI0ZIklJSUtS9e/eAmurqau3bt8+uAQAACOmnzBYtWqQHH3xQt99+u2pqavTzn/9c9fX1mjFjhhwOh3JycpSfn6+kpCQlJSUpPz9fN998s7KysiRJLpdLs2bNUm5urnr37q3o6GgtWrTIvgQHAAAghXggOn78uH7wgx/or3/9q2677TYNHz5c5eXl6tu3ryTpmWeeUWNjo+bOnava2lqlpqZq48aNioyMtI+xdOlShYWFadq0aWpsbNS4ceO0Zs0adevWLVjTAgAAISakA1FJSclF9zscDuXl5SkvL6/dmh49eqiwsFCFhYXXuDsAAHCj6FL3EAEAAFwPBCIAAGA8AhEAADAegQgAABiPQAQAAIxHIAIAAMYjEAEAAOMRiAAAgPEIRAAAwHgEIgAAYDwCEQAAMB6BCAAAGI9ABAAAjEcgAgAAxiMQAQAA4xGIAACA8QhEAADAeAQiAABgPAIRAAAwHoEIAAAYj0AEAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAAGA8AhEAADAegQgAABiPQAQAAIxHIAIAAMYjEAEAAOMRiAAAgPEIRAAAwHgEIgAAYDyjAtEbb7yhfv36qUePHkpJSdF///d/B7slAAAQAowJRG+//bZycnL03HPP6bPPPtN3v/tdTZ48WceOHQt2awAAIMiMCURLlizRrFmz9Pjjj2vgwIFatmyZEhMTtXz58mC3BgAAgiws2A10hqamJlVUVOhf/uVfAsYnTpyobdu2tfkev98vv99vv/b5fJKk+vr6NuvPnWu5Rt2GrvbmfilnzzZf405CS0fPiyQ1N/svXdSFdfTc+P3fXONOQk9Hz803jX+7xp2Eno6em7+dOXONOwk9HT03DadPX+NOQk975+b8uGVZFz+AZYC//OUvliTrj3/8Y8D4Sy+9ZPXv37/N9zz//POWJDY2NjY2NrYbYKuqqrpoVjBiheg8h8MR8NqyrFZj5y1evFgLFy60X587d05ff/21evfu3e57Okt9fb0SExNVVVWlqKiooPYSajg37ePctI9z0z7OTds4L+0LtXNjWZZOnz6thISEi9YZEYhiYmLUrVs3eb3egPGamhrFxcW1+R6n0ymn0xkwduutt16vFjskKioqJH7ZQhHnpn2cm/ZxbtrHuWkb56V9oXRuXC7XJWuMuKk6PDxcKSkpKi0tDRgvLS3ViBEjgtQVAAAIFUasEEnSwoULlZ2drWHDhiktLU2/+c1vdOzYMT355JPBbg0AAASZMYFo+vTpOnXqlF544QVVV1crOTlZH374ofr27Rvs1q6Y0+nU888/3+qSHjg3F8O5aR/npn2cm7ZxXtrXVc+Nw7Iu9RwaAADAjc2Ie4gAAAAuhkAEAACMRyACAADGIxABAADjEYi6qJkzZ+rhhx8Odhshh/MSqL3zsWXLFjkcDtXV1XV6T6HE6/Xq6aef1l133aUePXooLi5O999/v37961/rb3+78f9m2MXMnDlTDoej1Xb48OFgtxY03z4n3bt3V1xcnCZMmKDf/va3OnfuXLDbC7r2fmfS09OD3dplMeaxewD4tj//+c8aOXKkbr31VuXn52vw4ME6e/as/ud//ke//e1vlZCQoMzMzGC3GVTp6elavXp1wNhtt90WpG5Cw/lz0tLSohMnTsjj8ejpp5/Wf/zHf+j9999XWJjZ/6y29TvTVR6/N/u/HABjzZ07V2FhYdq9e7ciIiLs8cGDB2vq1KmX/svYBnA6nXK73cFuI6R8+5z83d/9nf7+7/9ew4cP17hx47RmzRo9/vjjQe4wuLry7wyXzAAY59SpU9q4caPmzZsXEIa+Ldh/xBldx9ixYzV06FC9++67wW4FV4FABNzgfv/73+uWW24J2CZPnhzstoLq8OHDsixLAwYMCBiPiYmxz9FPf/rTIHUXOi783fn+978f7JZC1ne+8x0dPXo02G0EXVv/v3nxxReD3dZl4ZIZcIMbM2aMli9fHjC2Y8cO/fCHPwxSR6HjwlWgnTt36ty5c3rsscfk9/uD1FXouPB3p73VNEiWZbGqqLb/fxMdHR2kbq4MgQi4wUVEROiuu+4KGDt+/HiQugkNd911lxwOh7744ouA8TvuuEOS1LNnz2C0FXLa+t1B2w4cOKB+/foFu42g68q/M1wyA2Cc3r17a8KECSoqKtKZM2eC3Q66uM2bN2vv3r2aOnVqsFvBVWCFCICR3njjDY0cOVLDhg1TXl6ehgwZoptuukm7du3SF198oZSUlGC3iBDk9/vl9XoDHrsvKChQRkaG/umf/inY7QXd+fPzbWFhYYqJiQlSR5ePQNRFnTt3zvjvuwCuxp133qnPPvtM+fn5Wrx4sY4fPy6n06lBgwZp0aJFmjt3brBbRAjyeDyKj49XWFiYevXqpaFDh+r111/XjBkzdNNNXHQ5f36+bcCAAa0uT4cih8WXbXRJ6enpuuuuu1RUVBTsVgAA6PKIs11MbW2tPvjgA23ZskXjx48PdjsAANwQuObSxfzzP/+zdu3apdzcXD300EPBbgcAgBsCl8wAAIDxuGQGAACMRyACAADGIxABAADjEYgAAIDxCEQAAMB4BCIAkJSXl6d77rkn2G0ACBICEYAbgtfr1fz583XHHXfI6XQqMTFRDz74oP7rv/4r2K0B6AL4YkYAXd7Ro0c1cuRI3XrrrXrllVc0ZMgQNTc366OPPtK8efM67e8oNTc3q3v37p3yWQCuLVaIAHR5c+fOlcPh0M6dO/WP//iP6t+/v+6++24tXLhQ5eXlkqRjx47poYce0i233KKoqChNmzZNJ06caPeY586d0wsvvKA+ffrI6XTqnnvukcfjsfcfPXpUDodD//7v/67Ro0erR48eKi4uvu5zBXB9EIgAdGlff/21PB6P5s2bp4iIiFb7b731VlmWpYcfflhff/21tm7dqtLSUv3v//6vpk+f3u5xX3vtNb366qv65S9/qT179mjSpEnKzMzUoUOHAup++tOfasGCBTpw4IAmTZp0zecHoHNwyQxAl3b48GFZlqXvfOc77dZs2rRJe/bs0ZEjR5SYmChJWrt2re6++27t2rVL9957b6v3/PKXv9RPf/pTPfroo5Kkf/u3f9PHH3+sZcuW6Ve/+pVdl5OToylTplzjWQHobKwQAejSzv85RofD0W7NgQMHlJiYaIchSRo0aJBuvfVWHThwoFV9fX29vvrqK40cOTJgfOTIka3qhw0bdjXtAwgRBCIAXVpSUpIcDkebweY8y7LaDEztjZ934b626tu6TAeg6yEQAejSoqOjNWnSJP3qV7/SmTNnWu2vq6vToEGDdOzYMVVVVdnjn3/+uXw+nwYOHNjqPVFRUUpISFBZWVnA+LZt29qsB9D1cQ8RgC7vjTfe0IgRI3TffffphRde0JAhQ3T27FmVlpZq+fLl+vzzzzVkyBA99thjWrZsmc6ePau5c+dq1KhR7V7y+slPfqLnn39ed955p+655x6tXr1alZWVWrduXSfPDkBnIBAB6PL69eunTz/9VC+99JJyc3NVXV2t2267TSkpKVq+fLkcDofee+89zZ8/Xw888IBuuukmpaenq7CwsN1jLliwQPX19crNzVVNTY0GDRqk999/X0lJSZ04MwCdxWGdvyMRAADAUNxDBAAAjEcgAgAAxiMQAQAA4xGIAACA8QhEAADAeAQiAABgPAIRAAAwHoEIAAAYj0AEAACMRyACAADGIxABAADj/f/ZzxHPlTVCiAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x= color['Color'],y=color['Price'], palette='bone')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87827bd4-b535-41b3-8431-e255a054b7c6",
   "metadata": {},
   "source": [
    "#### -> we see the average price for each color "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3feb680e-d3f9-41be-9c42-cf57d7352993",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Clarity</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SI2</td>\n",
       "      <td>3760.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>I1</td>\n",
       "      <td>3296.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SI1</td>\n",
       "      <td>3260.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>VS1</td>\n",
       "      <td>3142.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>VS2</td>\n",
       "      <td>3092.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>VVS2</td>\n",
       "      <td>2782.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>VVS1</td>\n",
       "      <td>2125.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>IF</td>\n",
       "      <td>2119.54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Clarity    Price\n",
       "0     SI2  3760.29\n",
       "1      I1  3296.18\n",
       "2     SI1  3260.29\n",
       "3     VS1  3142.50\n",
       "4     VS2  3092.77\n",
       "5    VVS2  2782.27\n",
       "6    VVS1  2125.65\n",
       "7      IF  2119.54"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clarity = df.groupby('Clarity').mean().sort_values('Price',ascending=False)\n",
    "clarity = clarity[['Price']].round(2)\n",
    "clarity.reset_index(inplace=True)\n",
    "clarity "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "23bba7ca-de3a-4332-97cf-c30f9b11aa83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x= clarity['Clarity'],y=clarity['Price'], palette='bone')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a0b5386-400f-4b7c-912f-20e773c5efc1",
   "metadata": {},
   "source": [
    "#### -> we see the average price for each clarity degree "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "490b0846-2b4b-4cb7-a38c-cf708fba4fc1",
   "metadata": {},
   "source": [
    "-----------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "851a4483-f99f-4300-97c0-b3b331e999f4",
   "metadata": {},
   "source": [
    "### Data correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ebe4d289-c126-44be-8606-f65dfb409f3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.corr(),annot = True,cmap='bone')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b94b8fbf-27b6-486b-bbc9-ee47bd109b78",
   "metadata": {},
   "source": [
    "_________________"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe12a087-6cf1-4691-979c-a551df04d30c",
   "metadata": {},
   "source": [
    "## Building ML models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "0394a873-f54d-4e7a-9f0d-d274f521f66b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler \n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.linear_model import Ridge \n",
    "from sklearn.linear_model import Lasso\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.preprocessing import OrdinalEncoder\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "178f6184-ca6a-43fe-9a05-3f8042afa629",
   "metadata": {},
   "source": [
    "### Data preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca584a80-727d-466b-a8dd-2de380efa086",
   "metadata": {},
   "source": [
    "#### Encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f35e42fa-027f-400b-8768-85136b72cb08",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Cut_Quality'] = df['Cut_Quality'].map({'Fair':0, 'Good':1, 'Very Good':2, 'Premium':3, 'Ideal':4})\n",
    "df['Color'] = df['Color'].map({'J':0, 'I':1, 'H':2, 'G':3, 'F':4, 'E':5, 'D':6})\n",
    "df['Clarity'] = df['Clarity'].map({'I1':0, 'SI2':1, 'SI1':2, 'VS2':3, 'VS1':4, 'VVS2':5, 'VVS1':6, 'IF':7})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44c99dde-ac96-42dd-972f-04bbc675cab8",
   "metadata": {},
   "source": [
    "### Split data [feature - target] feature selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6d5a54c7-f0cd-4529-9a52-01aa79ddc133",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=df[['Weight', 'Cut_Quality', 'Color', 'Clarity',  \n",
    "       'X_length', 'Y_width', 'Z_Depth']]\n",
    "y=df[['Price']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd3c1832-d723-4c97-9b8d-9ac1bc9368fc",
   "metadata": {},
   "source": [
    "##### -> from  the corrrelation heatmap : the relation between  [Depth - Taple] features with the target we didn't put it in 'x' list (features passed to the model) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a01f2b6b-4da6-4c55-aa42-eaa9538f1048",
   "metadata": {},
   "source": [
    "### Scalling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f2ad5e60-2d70-4f59-b19a-5cb0f95aaed2",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "x= scaler.fit_transform(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78560812-b76e-410e-9ae5-0b3d061bd482",
   "metadata": {},
   "source": [
    "### Split data [train - test]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "21695037-8344-482f-a98b-fecd83cf0bd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train , x_test , y_train , y_test = train_test_split(x,y,test_size=.2,shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14c4a0cd-3a75-4a0f-b63e-fd4a8df0f2aa",
   "metadata": {},
   "source": [
    "----------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f7d0e27-3bce-4d09-b862-1c3f1af2bc26",
   "metadata": {},
   "source": [
    "### Model build "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc6e1d94-c58e-438e-9fc5-8450c93e0b4c",
   "metadata": {},
   "source": [
    "------------------------\n",
    "### Regression model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7e3ef095-a87d-4501-8e3a-b9c294810e4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "51c3b597-a93d-4cfd-8b6a-3ec652cdebc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "00620138-6b10-4b5b-b628-fe3873e0b4ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "cff282c9-93ca-4490-9528-163309966ace",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The train accuracy : 0.9151818749809592\n",
      "The test accuracy : 0.9114131841326967\n"
     ]
    }
   ],
   "source": [
    "print(f''' The train accuracy : {r2_score(y_train,model.predict(x_train))}\n",
    "The test accuracy : {r2_score(y_test , y_pred)}''')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8de179ea-f831-4edc-847a-04d3176b3773",
   "metadata": {},
   "source": [
    "### Ridge model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "32f36727-0bf0-4af4-802f-fb801822e047",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ridge(alpha=2)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_model = Ridge(alpha=2)\n",
    "r_model.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "83799d4e-48cf-463f-a475-74262221493e",
   "metadata": {},
   "outputs": [],
   "source": [
    "rg_pred = r_model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4bafb9f8-d304-48bc-a871-b8d827710b96",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The train accuracy : 0.9151808700998215\n",
      "The test accuracy : 0.9114022631166341\n"
     ]
    }
   ],
   "source": [
    "print(f''' The train accuracy : {r2_score(y_train,r_model.predict(x_train))}\n",
    "The test accuracy : {r2_score(y_test,rg_pred)}''')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1f26c0e-ff37-452a-be26-8bcac0e4996b",
   "metadata": {},
   "source": [
    "### Lasso model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "206abddc-2b61-42ec-bb02-1468115739a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lasso(alpha=2)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l_model = Lasso(alpha=2)\n",
    "l_model.fit(x_train , y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "fcc174ac-2a34-45c7-95e4-b01e41f3d770",
   "metadata": {},
   "outputs": [],
   "source": [
    "ls_pred = l_model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "81880a1b-c4e1-48f7-a2a8-281d0599a927",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The train accuracy : 0.9148186883254528\n",
      "The test accuracy : 0.9107726295925066\n"
     ]
    }
   ],
   "source": [
    "print(f''' The train accuracy : {r2_score(y_train,l_model.predict(x_train))}\n",
    "The test accuracy : {r2_score(y_test,ls_pred)}''')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7b05ebd-4166-4ab1-9878-60b0739d1cf2",
   "metadata": {},
   "source": [
    "### Polynomial Regression "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8b3172b2-0ed9-4ffc-b95d-43ec528ee3b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "polynomial = PolynomialFeatures(degree=3)\n",
    "x_poly = polynomial.fit_transform(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "584a6684-69fb-41e8-bfda-29302f57c693",
   "metadata": {},
   "outputs": [],
   "source": [
    "p_x_train , p_x_test , p_y_train , p_y_test = train_test_split(x_poly,y,test_size=.2,shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "d3c58b7c-f920-4765-9d76-cb961b3cc563",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model2 = LinearRegression()\n",
    "model2.fit(p_x_train,p_y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "487966e7-5273-42fe-a1ff-bf9fe66ece43",
   "metadata": {},
   "outputs": [],
   "source": [
    "p_pred = model2.predict(p_x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9d8b95d0-6b80-49d4-859d-82571365d1af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The train accuracy : 0.9784012285108165\n",
      "The test accuracy : 0.9748440293196369\n"
     ]
    }
   ],
   "source": [
    "print(f''' The train accuracy : {r2_score(p_y_train,model2.predict(p_x_train))}\n",
    "The test accuracy : {r2_score(p_y_test,p_pred)}''')\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7dd1f1ca-c595-4228-9feb-0a6b677628d9",
   "metadata": {},
   "source": [
    "### Random forest regression model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "f6b355b2-6d32-45fa-96da-23a13bce7602",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor()"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_forest = RandomForestRegressor(n_estimators=100)\n",
    "random_forest.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "8ae4487f-35d2-49db-bd89-8469c98fdaed",
   "metadata": {},
   "outputs": [],
   "source": [
    "random_f_pred = random_forest.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "e5178746-9b57-4c7b-8835-07e26312412c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9829248630505233"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_test,random_f_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2dd75da-f3f3-4a67-85d1-e3e836f26201",
   "metadata": {},
   "source": [
    "------------------\n",
    "### Cross validation apply on Regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a4617c92-6316-4c7c-a6e2-73b0a220028b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The accuracy of cross validation applying on regression model :  0.9151045263881336\n"
     ]
    }
   ],
   "source": [
    "scores = cross_val_score(LinearRegression(),x_train, y_train ,cv=6)\n",
    "print('The accuracy of cross validation applying on regression model : ',scores.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2546f4be-6187-46c0-bd70-917e676dc805",
   "metadata": {},
   "source": [
    "------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd114d62-5c1c-4689-b282-4dd535fc61f5",
   "metadata": {},
   "source": [
    "###  Results \n",
    "#### - We achived [.98] accuracy value by the [Random Forest Regressor ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0aabb693-8283-4436-9f02-b6bd2c010dcd",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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